# Falcon Information Language: en > Falcon provides website development, AI system development, and SEO/GEO search growth services for Taiwanese companies, with a focus on verifiable case studies, technical quality, and qualified inquiries. ## Key services ### Website development and software development | Corporate websites, e-commerce, customized systems URL: https://www.falconinformation.com/en/services/web-development Falcon provides customized development for corporate websites, e-commerce platforms, CMS/ERP systems, and apps. We use Next.js, React, and TypeScript, with permanent after-sales support and source code ownership for the client. Falcon uses Next.js + React modern technology stack to create customized websites. We don't handle template-based websites – if your budget only allows for self-built websites using templates, we're not the right choice. However, if you need a website that can be long-term managed, SEO-friendly, and easily expanded or transferred to another vendor, please continue reading. Our principle is simple: we provide you with complete source code and do not engage in data hoarding. - Types of websites we create - Corporate website (5–10 pages, brand presentation + SEO optimization) - E-commerce platform (payment gateway integration, membership system, backend management) - Customized SaaS / Software Platform - CMS (Content Management System) - ERP (Enterprise Resource Planning) - App development (iOS + Android) - Technology selection and delivery - Frontend: Next.js 16 + React 19 + Tailwind CSS - CMS backend: Choose based on needs (customers can update content themselves) - Deployment: Vercel / Cloudflare / Customer-owned servers - Responsive design (mobile / tablet / desktop) - Complete source code delivery, no vendor lock-in - Permanent after-sales warranty (minor modifications are not charged extra) - Website speed is not just a technical issue, it's a business issue "A slightly slower website doesn't matter?" It does. Each extra second of loading time increases the bounce rate and the likelihood of users abandoning the site. This directly impacts e-commerce sales and can deter potential customers from even seeing your site. Google also considers page load speed (Core Web Vitals) as a ranking factor, meaning a slow website has fewer opportunities to be seen. That's why we insist on using modern frameworks like Next.js, treating performance as a default rather than an afterthought. We incorporate server-side rendering, image compression, and caching during development. Many low-cost template websites suffer from issues that aren't immediately apparent, such as slow speeds caused by unnecessary plugins and bloated code. These are difficult to fix later on. - Our perspective: A website is an asset, not a one-time expense Cheap template websites are expensive in the long run – your data is tied to the platform, adding new features can be difficult, and changing the design requires a monthly fee. Our approach is to view a website as an "asset." It needs to be able to: be modified by you, be found by Google and AI search engines, and be easily transferred or maintained if you choose to switch vendors or manage it yourself. When we deliver, we provide the source code, design files, and backend accounts. While customizing may be more expensive than using a template in the short term, the savings in binding costs and rework over three years often outweigh the initial investment. - When calculating the cost of a website, consider a three-year period, not just the initial setup fee The development fee on a quotation covers only part of the first year’s cost. A website’s total ownership cost also includes annual domain registration, hosting, SSL certificates, content updates and necessary maintenance. We recommend considering development cost + annual operating cost × 3 years. Some plans are cheap initially but charge separately for features or lock you into expensive monthly fees, making the three-year total higher. We explain pricing and deliverables upfront: you receive the source code and administration system, hosting and domains can be registered in your name, and you can maintain the site yourself or engage us. Costs depend on specifications and traffic, but you can estimate the three-year budget without unexpected charges after a low introductory price. - Actual projects We don't rely on adjectives to convince you; instead, see the websites we've built: Hualien Taxi Dispatch Platform (hualientaxi.taxi, including AI call handling and backend dispatch), ESCROWA Global Game Trading Platform (escrowa.com.tw, bilingual CMS), Honwei Commercial Real Estate Website + CMS (allenlo.com.tw), CosmosWork Case Matching Platform (falcontaskbridge.com), invisible care Home Cleaning Brand Website + CMS (needfix.com.tw). More case studies can be found in the "Portfolio" section on the homepage. - How much does a website cost? Requirements can vary substantially: corporate websites cost TWD 20,000–37,500; e-commerce platforms TWD 45,000–125,000; and custom systems (CMS/ERP) TWD 75,000–250,000 or more. We recommend an initial consultation, followed by a quote based on the complexity of your needs. - How long does it take to build a website? Company website: 4–6 (weeks); E-commerce platform: 8–12 (weeks); Complex systems: 3–6 (months). The actual timeline depends on the complexity of the requirements and the speed of feedback from both parties. - Can I edit the content on the website after it's launched? Yes. We provide a CMS back-end that allows you to edit text, images, and add new pages, without requiring any programming knowledge. We also provide training on how to use the system. - Who owns the website? The website is fully owned by the client. We deliver the source code, design files, and CMS account. You will have no issues transferring to a different vendor or maintaining it yourself in the future. - What is the scope of the after-sales warranty? Permanent after-sales support: Bug fixes and minor text/image updates are free. Larger feature expansions will be quoted separately. - Is an SSL certificate (HTTPS) required for the website? Does it cost extra? Yes, browsers will mark websites without HTTPS as "insecure," which also affects SEO. Fortunately, most image-based websites can use the free Let's Encrypt certificate, which we will install and automatically renew for you upon delivery, at no extra cost. We only recommend upgrading to paid OV/EV certificates in special situations (such as financial institutions or large e-commerce businesses that require enterprise validation), and we will clearly explain the differences without resorting to scare tactics. - Should I choose WordPress or custom development? It depends on the needs. WordPress is a mature, open-source system with a rich ecosystem and a quick learning curve. It is a practical choice for content-based websites or when budget is a priority. Custom development (using Next.js) offers more flexibility and scalability, especially for websites that require long-term operation, unique processes, or high traffic. We won't tell you which is "better," but rather ask you what problem you need to solve, and then recommend the appropriate solution. - How to understand different vendors' quotes? Don't just compare the total price, compare what you get for the same price. We recommend comparing these points: number of pages and whether it is customized, what content can be modified in the backend, whether it includes basic SEO, who owns the source code and materials, how to calculate acceptance and modification times, and the conditions for maintenance and renewal after launch. It's common to find prices that are close but the content is very different. By clarifying these points, you can avoid discovering that you need to keep adding money after the website goes live. ### AI Tool Development | Customer Service Robots, Intelligent Assistants, Business Automation URL: https://www.falconinformation.com/en/services/ai-tools Falcon provides customized AI tool development: AI customer service, voice-based call handling, knowledge base Q&A, document processing automation, sales assistant. Integrates with GPT, Claude, and Gemini APIs, and can be deployed on customer-owned servers. The key to successfully implementing AI tools is not "which model to use," but rather "identifying the highest ROI entry point." Our first step is to assess your processes and identify which tasks are suitable for AI to replace or assist with, and then decide whether to build it in-house or use a ready-made SaaS solution – not every process needs AI, and forcing it in can be a waste of resources. - Types of AI Applications We Offer - AI Customer Service / Intelligent Assistant (LINE, website, Slack) - AI Voice-Based Call Handling and Routing (real-time voice conversations, automated order creation) - Enterprise Knowledge Base Q&A System (employees asking questions about internal documents and SOPs) - Document Processing Automation (contract review, invoice recognition, report generation) - Customized GPT / Claude Assistants (specific domain knowledge) - Flexible Technology Choices - No Vendor Lock-in: Integrate with GPT, Claude, and Gemini, and choose the most suitable model for each task - Flexible Deployment: Use cloud APIs or deploy open-source models on customer-owned servers (data remains private) - Full Source Code Delivery, No Long-Term Licensing Fees - Experience integrating with LINE, Slack, and customer-owned backend systems - How accurate are AI customer service bots? The key is RAG, putting answers into your own knowledge base The most common concern customers have is, "Will the AI give incorrect answers?" Yes, this is inherent in language models – they are naturally prone to fabricating information ("hallucination") to make their responses sound correct. Our approach is not to pretend this problem doesn't exist, but to manage it within acceptable limits using RAG (Retrieval-Augmented Generation): first, break down your product documentation, FAQs, and SOPs into smaller segments and create vector indexes. When a user asks a question, the system first "retrieves information" and then allows the AI to "answer based on the retrieved content," with citations provided. If it cannot answer, we honestly admit, "I'll connect you with a human," rather than making things up. We prioritize transparency: RAG reduces error rates and makes answers traceable, but it doesn't guarantee zero errors. For high-risk questions (financial, legal, medical), we always retain human oversight. - What to do when the AI can't answer: transferring to a human and designing the conversation flow A good AI customer service system is valuable not only for what it can answer, but also for how it handles situations where it cannot. We design escalation rules: if the AI answers incorrectly twice in a row, if the user uses emotional language, or if they ask about sensitive topics like payments and refunds, we automatically transfer the complete conversation to a human, so the customer doesn't have to repeat themselves. The conversation flow is hybrid – fixed processes (checking orders, making reservations, reporting issues) follow rules to ensure accuracy, while open-ended questions are handled by the AI, using intent recognition and multi-turn memory to understand the context (e.g., if the user asks "How long will it take to return?", then "How many days?", the system understands that both questions refer to the same thing). Pure decision trees are too rigid, and letting the AI run completely wild can lead to unpredictable results. The best approach is to find a balance. - Our perspective: Focus on ROI, not just AI for AI's sake A common situation is that business owners see news about AI and think, "We should implement it too," but they don't know what problem it will solve. Our approach is the opposite: we first identify the "repetitive, labor-intensive, and rule-based" areas where the ROI is most easily calculated. For example, we implemented AI voice answering for a taxi fleet in Hualien, where a large number of calls were handled by repetitive human labor. The AI can handle both immediate voice conversations and automatically dispatch vehicles based on pre-defined rules. This is a cost-effective solution. On the other hand, if you simply want a "impressive-looking" AI, we will honestly tell you that it's not worth the investment. - Real-world AI projects We have delivered AI applications, including the AI phone answering and SmartDispatcherV2 backend for GoGoCha Hualien taxis, multi-model deployment of Claude/Gemini/OpenAI for the dating game Alive, and the 7 emotional support system, which are available on iOS/Android; as well as LINE appointment systems for traditional Chinese medicine clinics (including concurrent control and a large number of E2E tests). These are real systems that are currently in operation, not demos. - How much does it cost to develop an AI customer service system? The MVP version has a one-time fee of approximately TWD 30,000, plus a monthly API fee of TWD 10,000–30,000 (API fees reflect the actual usage costs of third-party services and are not discounted). Customized, complex versions range from TWD 75,000 to TWD 125,000. The specific price depends on the required features and the complexity of integration. - How long does it take to develop an AI customer service system? The MVP typically takes 3–4 weeks; full customization takes 6–12 weeks. Using agile development, you can usually see a working prototype by the second week. - Why should I hire you to develop an AI customer service system instead of using ChatGPT myself? If you are using it for personal assistance, using ChatGPT yourself is fine. Customized development is suitable for: shared use by employees/customers, connecting to internal data, integrating with existing systems, and complying with data compliance requirements. We recommend first consulting to determine which category your needs fall into. - Will customer data be leaked? We design based on the sensitivity of the data: low sensitivity can use OpenAI/Anthropic APIs (with data retention policies); high sensitivity can deploy open-source models on your own servers, ensuring complete data control. We have experience with developing medical appointment systems with concurrency control and testing, understanding the requirements for handling sensitive data. - Will the AI customer service system give incorrect or misleading answers? Language models inherently have "hallucinations" (making up information). We use RAG to limit the answers to your provided knowledge base, with source citations, and escalate to a human agent when unable to answer. This helps to minimize error rates. However, we do not guarantee "zero errors" – high-risk questions such as those related to finance and compliance will always require human oversight. - How can I tell if the AI customer service system is effective? Look at measurable operational metrics, not just "feeling smarter." Common metrics to track include: resolution rate (the percentage of conversations that are resolved without human intervention), first response time, customer satisfaction (CSAT), and changes in labor costs. The actual numbers will vary depending on your industry and the maturity of your knowledge base. We will discuss with you in advance which metrics to use and how to measure them, avoiding unrealistic promises. - Once the AI customer service system is launched, is that it? AI customer service is an ongoing process, not a one-time purchase. After launch, you need to regularly review incorrect conversations, fill in gaps in the knowledge base, and update the system with new product features. We provide the source code and maintenance documentation, so you can maintain it yourself or outsource it to us on a monthly basis. - How do I choose an AI customer service system or vendor? First, determine whether you need a "ready-made SaaS" or "custom development" – if you have standard requirements, a small team, and need to launch quickly, SaaS is more convenient. If you need to integrate with existing systems, keep your data on your own servers, or have unique processes, custom development is more suitable. When choosing a vendor, consider: whether they can use RAG to limit answers to your knowledge base, whether they have a mechanism for escalating to a human agent, who owns the source code and data, and how the system will be maintained after launch. Don't just be swayed by the "smartness" of the system; ask about what happens when it can't answer. ### AI Voice Customer Service System | Enterprise AI Phone, Routing, and CRM Integration URL: https://www.falconinformation.com/en/services/ai-voice-agent Falcon: Customized Enterprise AI Voice Customer Service and Automated Phone Systems: Integrate existing phone systems, routing, work orders, CRM, and manual handover processes. GoGoCha provides publicly available case studies demonstrating the scope of implementation. AI voice customer service is not simply about plugging a chatbot into a phone. Businesses truly need to ensure that the content of the call flows into a controlled workflow: obtaining necessary information, querying rules, creating work orders or tickets, synchronizing existing systems, and handing over to a human agent when the AI cannot confirm. Falcon provides this type of customized integration, and GoGoCha provides publicly available evidence of our implementation. - What is AI voice customer service? AI voice customer service is a software process that can recognize speech, understand tasks, generate responses, and interact with enterprise systems over the phone. Unlike traditional IVR systems that only play menus, it can handle more natural language and follow-up questions. However, it can still make mistakes, so financial information, identity verification, address details, and high-risk decisions require rule validation, low-confidence fallback, and manual handover. - We focus on systems that actually complete tasks, not just voice playback. If employees still need to manually transcribe or log into another system after the call, the AI simply replaces the answering function with a transcript. Falcon's focus is on converting the call results into work orders, tickets, or CRM actions, and ensuring that the same status is visible on the website, LINE, app, and backend. - Can AI voice customer service completely replace human agents? It is not recommended to use "complete replacement" as the primary goal. Automated systems are best suited for clear, repetitive queries and order creation. Complaints, financial transactions, compliance, identity disputes, and low-confidence conversations should be handled by humans. A good system first defines the handover conditions, rather than forcing the AI to continue indefinitely. - Can we continue to use our existing phone number or PBX? It is usually possible to evaluate using existing systems, but you need to confirm support from the telecom provider, virtual number, PBX/SIP, and the transfer method and recording requirements. These are custom requirements that need to be confirmed before the POC, and we cannot guarantee a direct connection without first assessing the environment. - What if the AI mishears an address, name, or order details? Important fields should be repeated and verified, and then the backend should perform format and business rule checks. If the AI cannot confirm, has low confidence, or encounters sensitive information, the context should be transferred to a human agent to avoid the user having to repeat everything. - How are AI phone systems priced? Customized quotes are provided. The cost depends on the direction of calls, concurrent lines, telecommunications and PBX systems, language, integration with enterprise systems, recording storage, number of operator seats, deployment, and SLA; as well as the actual usage of phone, voice recognition, voice synthesis, and models. - What capabilities does the GoGoCha case demonstrate? Publicly available data can demonstrate the AI phone entry, real-time dispatch backend, and integration with websites, LINE, driver/passenger apps, and operational backends. Unpublicized fleet revenue, labor savings, and actual call SLAs will not be used as performance claims. ### SEO: Search Engine Optimization | Technical Audit, Content Strategy, Backlink Analysis URL: https://www.falconinformation.com/en/services/seo Falcon provides technical SEO, search intent analysis, case study content, internal linking, and GSC/GA4 measurement, treating GEO as an extension of a unified search growth system. SEO is one of the few long-term channels that can generate organic traffic, besides paid advertising. A consistently ranking article can bring in visitors for several years, even monthly. However, it's important to understand that SEO has no shortcuts. Any company that promises you "top ranking in one month" is essentially gambling, and you, the website owner, are the one who loses. We prefer to be conservative in our expectations and avoid cases where rankings collapse after six months, leading to customer dissatisfaction. - Three Layers of SEO: Technical, Content, and Authority Technical SEO addresses the issue of "crawlability" – site speed, mobile experience, structured data, and crawler accessibility. Content SEO addresses the question of "whether the page provides what users are actually searching for." Authority SEO addresses the question of "whether external sources trust you" – backlinks, the frequency and quality of brand mentions. All three are essential, but our standard approach is "Technical → Content → Authority": building a solid foundation before focusing on external links is like pouring money into a leaky bucket. - How Search Engines Determine Rankings: Crawling, Indexing, and Ranking Many business owners see a lack of ranking improvement and immediately assume the content is not good enough. However, the problem often lies earlier in the process. In simple terms, Google performs three actions on a page: first, "crawling" (ensuring the crawler can access and read the page, and that it's not blocked or loads too slowly), then "indexing" (deciding whether to include the page in its database, and avoiding duplicate or empty pages), and finally, "ranking" (determining the order of the pages in the search results). This highlights a crucial fact: if your page fails at the crawling or indexing stage, no amount of good content will improve its ranking. That's why our audits start with a technical assessment to ensure your page has successfully navigated these three stages before focusing on content. - Falcon's Actual SEO Project Deliverables Not just "optimization," but concrete monthly results you can see: - Initial Full Site Audit: Core Web Vitals (including INP), Schema Structured Data, Mobile-First, Crawler Accessibility, Indexing Status - Keyword Research and Search Intent Classification (separating informational, commercial, and transactional searches) - Monthly Content Output (based on 4–15 plans, with one set of real queries per article) - White-Hat Backlink Acquisition: Building links through content and PR, avoiding paid link schemes - Google Search Console + GA4 Monitoring, Monthly Reports (easy-to-understand reports, not just PDF documents filled with jargon) - Can SEO be done by yourself? Which tasks are best handled internally, and which should be outsourced? Absolutely, and we genuinely recommend that you handle some aspects yourself. The key is to focus on the areas where your expertise is most valuable. We can assist with topic selection, keyword research, editing, and structuring content; however, basic Google Search Console setup and setting up your business profile can be easily done yourself. The areas where outsourcing is most beneficial are those that require specialized tools and experience, such as technical audits and fixes, schema markup implementation, backlink strategies, and developing a comprehensive search intent and internal linking strategy. Therefore, we won't force you to hand over everything to us. When budgets are limited, we'll instead help you prioritize and focus your resources on the areas where professional expertise is most needed. - Our perspective: GEO and AEO don't require separate foundations. Google's AI features still rely on its search index and quality system. Therefore, focusing on crawling, indexing, speed, content, and measurement is the foundation for both SEO and GEO. While FAQs can improve reader understanding, a business website cannot rely solely on FAQ pages or HowTo schema to achieve general Google rich results. AEO in Falcon's service simply provides a method for answering questions clearly, without offering a separate schema package. - SEO projects we don't take on It's more important to be clear about what we can and cannot do. We typically advise against working with us, or even starting a project, if it involves: guaranteeing first-page rankings within a month (this often involves black-hat techniques that are penalized by Google); requiring us to purchase a large number of backlinks or flood your website with low-quality content generated by AI (this is essentially sabotaging your website); or attempting to bypass SEO entirely and jump straight into GEO with a very limited budget and no existing content. This approach is likely to waste your money. - How long does it take to see results from SEO? There is no guaranteed fixed timeframe. Results are influenced by factors such as crawling and indexing, website history, competition, content quality, and external signals. We initially save the GSC and initial inquiry criteria, then check leading indicators and qualified inquiries monthly, without promising rankings within a few weeks. - Why do some SEO companies offer lower prices? Price differences may stem from the scope of work, content depth, technical investment, and reporting methods. Quality cannot be determined solely by price. Before signing a contract, you should ask the company whether they purchase backlinks, how they verify content, and whether their KPIs can consistently generate qualified leads. - How should SEO and Google Ads be allocated? Our typical recommendation: Use Ads to quickly test which keywords actually generate sales, and then hand those keywords over to SEO for long-term management. Once Ads are stopped, traffic will drop to zero, but SEO rankings can remain stable for several years. - Will AI search replace Google? Is SEO still relevant? SEO remains a crucial foundation for AI search. Google's official explanation of AI Overview and AI Mode uses search indexes and core quality systems. We manage both traditional and AI search with the same content, without creating artificial, AI-specific tags. - Our company is located in Taoyuan. Can we discuss this in person? Yes. Falcon works by appointment and can visit clients in Taoyuan, Taipei, New Taipei and Hsinchu as scheduling allows. We have no walk-in storefront; meetings with clients in other areas are primarily online. - Small and medium-sized businesses have limited budgets. How should keywords be selected? Focus on long-tail keywords. Instead of trying to rank for broad terms like "SEO," which are highly competitive and difficult to rank for, focus on specific long-tail keywords, such as "Taoyuan handmade noodles e-commerce website." These keywords have lower search volume but have clear user intent and are easier to rank for. Once you have established a collection of long-tail content, you can then target more competitive keywords. - Will AI search (AI Overview) reduce SEO traffic? While some queries may decrease click-through rates due to direct answers, the impact varies depending on the query. We consider factors such as brand exposure, click-through rates, AI functionality/platform referrals, and qualified leads, rather than treating "mentions" as a standalone measure of success. - How to choose an SEO company? What should you look for? Some practical checks: (1) Are the methods explained clearly, ethical and verifiable, or are they vague? (2) Do the reports provide understandable data and next steps, or just PDFs full of jargon? (3) Do they promise a guaranteed first-place ranking? If so, move on. (4) Are the content and accounts (GSC and GA4) registered in your name and transferable when you change providers? Price is only one factor; do not compare monthly fees alone. ### GEO AI Search Optimization | Improve visibility with SEO, evidence, and measurement URL: https://www.falconinformation.com/en/services/geo Falcon performs GEO using technical SEO, real-named authors, original case studies, and AI search measurement. It does not sell llms.txt, special AI schemas, or guarantee citations. GEO is an industry term for work on visibility in AI search. Under Google’s official 2026 guidance, AI Overview and AI Mode have no additional technical requirements or dedicated AI schema; pages must still be crawlable, indexable and eligible to display a snippet. Falcon treats GEO as an extension of SEO: first-hand case studies, named responsibility, clear sources and measurement can help content be discovered in Google AI, ChatGPT Search and Perplexity, but do not guarantee citations. - The Core Differences Between SEO and GEO SEO and GEO are not mutually exclusive fields. Google AI utilizes search indexes and core quality systems; ChatGPT Search and Perplexity also require accessible public pages. The main differences lie in measurement and context: SEO primarily focuses on non-branded queries, clicks, and inquiries; GEO focuses on AI search functionality exposure, platform referrals, and fixed query sets. The common foundation remains technical quality, real-world experience, and external trust. - Falcon GEO Service Scope This is the actual work we provide: - Crawling, indexing, canonicalization, internal linking, speed, and content visibility checks - Necessary schema for Organization, Website, Service, Article, and Breadcrumb that aligns with the visual presentation - Disclosure of real author, case evidence, update date, source, and limitations - Organize topics based on real customer problems, avoid creating multiple query variations - Establish verifiable benchmarks using available GSC Generative AI, Bing AI Performance, GA4, fixed query sets, and inquiries - Content should not just be "fluent" to be cited by AI – it needs data, quotes, and sources A team at Princeton University conducted research on GEO in 2023, where they took the same content and added statistical data, expert quotes, and verifiable sources, then tested the probability of being cited in a generative engine. The conclusion is that these "credibility-enhancing" writing styles actually increase the chances of being selected by AI. However, it's important to note that this is an improvement in "relative visibility" in a controlled experiment, which varies depending on the topic type (technical and data-driven topics benefit from citing sources, while lifestyle topics benefit from readability). This does not guarantee traffic or revenue. We have translated this finding into concrete writing practices: try to include verifiable numbers and sources for key arguments, use firsthand experience or expert opinions, and avoid vague adjectives. This is why we prefer to omit a single, unverified number rather than letting AI (and readers) perceive the content as untrustworthy. - Making AI "Recognize You": Brand Consistency and Third-Party Feedback Brand names, responsible parties, services, phone numbers, and public links must be consistent across the website, social media, customer case studies, and third-party data. If there is no physical store, using a rented address to create a LocalBusiness signal is not possible. External mentions should only be genuine collaborations, customer references, and professional participation, not buying accounts, spamming forums, or creating encyclopedic pages that do not meet the inclusion criteria. - The Correct Positioning of llms.txt: Keep it, but Google will ignore it Google’s Generative AI guidance from 2026-7 states that Google Search does not use llms.txt. Keeping or removing it does not improve Google rankings or visibility in AI features. There is no universal guarantee that other systems use it, so we treat it only as an inexpensive content summary, generated from the website’s existing content source. We do not present it as a core deliverable of paid GEO work. - How this website implements GEO This website only retains Organization, Website, Service, Article, and CreativeWork schema that aligns with visible content; articles use real authors, case evidence, and limitations, and robots.txt allows OAI-SearchBot and PerplexityBot. FAQs are still available to readers, but we no longer output FAQPage/HowTo/Speakable to claim AI search effectiveness. - How long will it take to see results with GEO? There is no guaranteed timeline. Crawling and indexing corrections can be quickly verified, but whether a brand is cited by AI functionality will be affected by the query, platform, existing authority, and content competition. We observed the same set of metrics using 7, 28, 56, and 90, and do not guarantee results within a few weeks. - Should GEO and SEO be done separately or together? The underlying signals overlap, and doing them separately will duplicate efforts. Our approach is to optimize content for both search engines simultaneously, avoiding conflicts between the two teams. If you already have an SEO agency, we can also fill in the gaps in AI readability. - How can I verify that GEO is actually effective? Prioritize using Search Console Generative AI reports and Bing AI Performance, which are visible through accounts, and compare with GA4's AI sources, a fixed query sample, and qualified queries. Each set of data is clearly labeled; incorrect citations will not affect rankings, and sampling will not impersonate the overall platform exposure. - I already have an SEO agency, can I just use your services for GEO? Yes. We will assess the AI readability of existing content and fill in the gaps, avoiding conflicts with existing SEO work. - Is it appropriate to start doing GEO on a brand that has little content? Generally, it's best not to start a separate GEO project. First, establish a clear website, a responsible person, real case studies, search volume measurements, and necessary SEO content. If your company is entirely online and does not interact with customers face-to-face, you should not create a Google My Business profile that does not meet the requirements for local SEO. - Does E-E-A-T affect "being cited by AI"? Yes, especially the Google AI Overview. The E-E-A-T (Expertise, Experience, Authoritativeness, Trustworthiness) framework, originally developed by Google to assess content quality, is often cited by AI summaries to determine credible sources. This means that content should have a named author with relevant experience, verifiable sources, and a consistent and positive brand image externally. These signals are useful for both SEO and GEO, and do not require separate strategies for each. - After implementing GEO, how can you measure the impact on traffic? First, check Google AI visibility and Bing citation pages, then track ChatGPT's utm_source=chatgpt.com, AI platform referrer, landing pages, CTAs, and inquiries in GA4. It's important to note that some links and app traffic may not be measurable, so reports should not assume that visibility or citations automatically translate into conversions. ## Public Case Studies ### Yijinxiang E-commerce System Case: Image Efficiency, Membership, and Promotion Backend URL: https://www.falconinformation.com/en/case-studies/yizhenxiang-commerce-performance To build an e-commerce and operational backend for established food brands, with a focus on measurable website efficiency, promotional flexibility, and data autonomy. Established food brands need more than just a storefront; they need a complete e-commerce system that can handle products, members, promotions, and content. The challenges are twofold: firstly, the large volume of product and promotional images can significantly impact the Largest Contentful Paint (LCP) if not properly managed; secondly, promotional rules are complex – multiple promotions running simultaneously, tiered member discounts, and overlapping coupon conditions – which, if hardcoded, would require developers to update the system for each new promotion, tying the operational pace to development timelines. - Build the e-commerce core using Next.js, GraphQL, PostgreSQL, and Redis: The frontend retrieves product, member, and promotional data through GraphQL, with each component modeled independently. Redis handles caching of frequently accessed data, reducing database load. - Prioritize image pipeline management: Original images uploaded are converted to modern formats and resized for different layouts during output. The frontend loads the corresponding versions based on the device, rather than directly handing the original images to the browser for scaling. - Optimize LCP resource loading: Verify the loading priority of the main image on the first screen, pre-load and size declaration, and set the performance target to LCP within 2.5 seconds, validating during delivery. - Promotional rules are managed in the administration system: 19 promotion types (such as spend thresholds, quantity thresholds, gifts and limited-time discounts) and 5 membership tiers form a composable rule model. Staff configure the conditions and schedules; at checkout, the backend calculates the amount from those rules. Launching a new promotion does not require a code change. - Image size Reduce 88.8% Technical measurements from publicly available records; not claims of revenue or organic traffic growth. https://yizhenxiang.com.tw/zh-TW - LCP < 2.5 seconds Performance goals at project delivery; actual values will still fluctuate based on page, device, and network conditions. https://yizhenxiang.com.tw/zh-TW - Operational rules 19 type of activity / 5 layer member System feature scale, which does not represent the revenue generated by activities or members. This page only references technical data that has been publicly disclosed in the Falcon portfolio. Since no GA4, GSC, or revenue data from the client is available and publicly disclosed, we cannot claim any commercial growth figures. - E-commerce Frontend, Product, and Content Pages - Membership, Activity, and Coupon Operational Rules - GraphQL API, Database, and Cache Integration - Image Output and Main Loading Path Optimization - Consumers enter the shopping process from product or promotional pages, with optimized versions of images loaded based on the device. - The frontend retrieves product, member, and promotional data through GraphQL, with frequently accessed data cached in Redis. - During checkout, the backend calculates the final amount based on membership tier, ongoing promotions, and coupon rules; multiple rules can be processed in a defined order, without calculating prices on the frontend. - Operational staff can maintain product, content, and promotional schedules from the backend, without requiring code updates or redeployment to activate the rules. - The number of image optimization figures only describes the technical asset differences, not derived revenue growth. - Performance metrics fluctuate based on page, images, device, network, and third-party services. They should not be considered fixed values. - The number of members and features represents the scope of the system, not actual usage or promotional effectiveness. - Promotional amounts are always calculated on the backend; the frontend display is for reference only to avoid inconsistencies in pricing during rule changes. - Brand, products, and the main shopping interface can be verified on a public website. - 88.8% represents the total file size before and after image optimization for a specific batch of products. This is a one-time technical measurement, focusing on the image assets themselves, not continuous monitoring data. - LCP target and feature scale are based on existing publicly available records. - No publicly available GA4, GSC, conversion rate, order, or revenue data is available. ### How to integrate AI voice customer service with real-time dispatch | GoGoCha technical case study URL: https://www.falconinformation.com/en/case-studies/gogocha-ai-dispatch Integrate the brand website, AI call center, instant dispatch, LINE Bot, and driver/passenger app into a single backend system. Users include elderly individuals, travelers, and corporate clients. Entry points may include phone, website, or LINE. The system must allow information to flow into a single dispatch process while maintaining the ability for human intervention. - Send information obtained from the AI call center to a shared backend, preventing the phone entry from becoming an isolated data silo. - Build the instant dispatch backend using Express, PostgreSQL, Redis, BullMQ, and Socket.IO. - The website fare calculation should first call a real-time fare API. If the API fails, provide a clear alternative result based on local rules. - Design the interface for elderly users with large fonts, voice priority, and high contrast. - Dispatch product goals 3 seconds The product functionality goals do not mean that all real ride requests can be accepted by drivers within three seconds. https://hualientaxi.taxi/ - Primary entry points Phone/Website/LINE The three entry points share a common backend process, covering the system's scope. - Accessibility design Large font size and high contrast Based on the publicly available interface functionality, this does not equate to a third-party accessibility certification. This page describes the publicly available product capabilities and the Falcon technical scope; it does not disclose fleet revenue, order volume, time savings, connection rates, or call recordings or call SLAs. "3 seconds" is a product design goal, not a guarantee that every ride request can be accepted by a driver within three seconds. - Brand website and fare calculation interface - AI call center entry and task data structure - SmartDispatcherV2 – instant dispatch backend - Integration of LINE Bot, driver/passenger app, and operational backend - Users can submit ride requests via phone, website, or LINE. - The system collects location, contact, and task information and sends it to the shared dispatch process. - The backend uses PostgreSQL to store status, BullMQ to handle queues, and Redis/Socket.IO for real-time synchronization. - Drivers, passengers, and the operational interface all have access to the same task status. - Maintain human intervention when information is insufficient or the AI cannot reliably confirm, and do not treat guesses as dispatch data. - When the website fare API fails, display local rules and limitations, and do not pretend that a formal quote has been successful. - Use queues and real-time communication to handle connections in layers, preventing a single connection failure from resulting in the task being lost. - Users can verify phone, website, LINE, and fare calculation entry points through the public brand website. - Use the public app screen and website screen to demonstrate the range of products accessible through different entry points. This does not include private passenger or driver data. - The technical architecture is based on the actual scope of responsibility for Falcon; it does not disclose operational volume, connection rates, time savings, or formal SLAs. ### Clinic LINE appointment system case: concurrency control, real-time synchronization, and 130+ testing URL: https://www.falconinformation.com/en/case-studies/clinic-line-booking Using LINE LIFF to integrate patient appointment and clinic management backend, focusing on simultaneous bidding, time slot changes, and real-time synchronization between the front and back ends. The biggest risk with the appointment system is not the visual appearance of the interface, but the competition in the data layer: two patients submitting the same time slot at the same time, the clinic temporarily closes but the patient still sees the old time slot, or the front desk updates the appointment rules but the LINE still allows it. These scenarios will not occur during demonstrations, but will definitely occur under real traffic. The core of this project is to treat the "appearance of being able to book" and the "actually booking in the database" as two separate tasks, and to ensure that any changes in the backend are immediately reflected on the patient's end. - Booking with database locking and transaction processing: lock the time slot within the transaction when booking, and only the first party to obtain the lock will succeed, while the other party will receive a clear failure message, preventing the false appearance of both parties succeeding. - Frontend Status: The available time slots displayed are just a reference. The only definitive confirmation of a booking is a re-check by the backend system – whether the slot is still open, whether the patient meets the criteria, and whether there is a conflict with existing bookings. This re-check is performed on the server-side. - Using Supabase Realtime for Synchronization: When the backend changes clinic hours or rules, changes are immediately pushed to the open patient interface, reducing information discrepancies. However, the backend check remains the final authority. Realtime is responsible for the user experience, not for accuracy. - Writing Exception Scenarios as End-to-End Tests: Scenarios such as simultaneous booking attempts, immediate cancellation after booking, temporary clinic closures by the backend, re-checks after rule changes, and re-sending after connection loss should all be created as repeatable tests, allowing for full verification each time a change is made. - End-to-end testing 130+ The number of test cases listed in the publicly available data does not guarantee zero defects or medical effectiveness. - Consistency of appointments Database concurrency control Avoid conflicts arising from backend transactions; do not rely on a first-come, first-served approach in the frontend. - Synchronous method Realtime Appointment status and backend changes are updated in real-time. Customer names and internal operational data are not disclosed; this page only presents the technical range and test quantities that have been disclosed in existing product catalogs. - Patient Booking Process via LINE LIFF - Clinic Time and Booking Management Backend - Supabase Realtime Real-time Synchronization - Database Concurrency Control and End-to-End Testing - The patient opens the LINE LIFF booking interface, which loads the currently available time slots. This list is only a visual reference and not the final authority. - When a booking is submitted, the backend re-checks the availability of the time slot, booking rules, and potential conflicts within the same transaction. Only if all checks pass is the booking written. - When two people simultaneously attempt to book the same time slot, the database transaction determines the winner. The unsuccessful end receives a clear message and reloads the latest available time slot. - Realtime synchronizes time slot changes and backend updates to both the patient and clinic management interface, ensuring that both sides see the same status. - When multiple people simultaneously select the same time slot, the backend transaction result determines the winner. The unsuccessful end must re-select, without assuming "first come, first served." - When a connection is interrupted, it is not assumed that the booking was successful. The display must re-query the backend status before displaying the results. - The effective time for rule changes is determined by the server-side, and if the patient's display has not been updated, the booking will still be rejected by the backend check. - The anonymous case does not disclose patient, clinic, booking volume, or medical information, nor does it claim any medical or operational results. - The 130+ end-to-end testing scenarios cover: normal booking and cancellation, simultaneous booking attempts with concurrency, backend time slot changes and temporary closures, booking checks after rule changes, connection loss and re-sending. - The test numbers represent the number of cases documented in existing public works, not a guarantee of zero defects. - Database locking, transactions, and Realtime describe system design, not any operational commitment. - Customer names, patient data, booking volume, and operational metrics are not disclosed. ## Pricing page ### Website development costs | Quotes for corporate websites, e-commerce, and custom systems URL: https://www.falconinformation.com/en/pricing/web-development Website setup costs: Official website - starting from TWD 20,000, e-commerce platform - starting from TWD 45,000, custom system - starting from TWD 75,000. This page explains how to allocate one-time setup costs and ongoing costs, ownership of source code and accounts, and pricing for common add-on items. Corporate Image Website: TWD 20,000 per project; pricing for e-commerce and custom systems varies depending on functionality, data, and integration complexity. The prices listed above are starting prices, and not all requirements can be fulfilled at the same price – a formal quote will specify the range for each item, the number of revisions, and what is not included. - Besides the one-time setup fee, what are the ongoing costs? The total cost of a website is not just the setup fee. Looking at it over a three-year period, there are at least four additional costs: domain registration fees, hosting or cloud fees, certificate and email services, and content updates and maintenance. We will list these separately, with one-time costs for one-time costs and annual fees for annual fees, so you can compare them item by item with other quotes, rather than just comparing the total price of the first month. Some quotes may seem cheaper because they hide the hosting and maintenance costs within the annual renewal fees. - One-time: Design, Development, Testing, Deployment, Training - Annual: Domain, Hosting/Cloud, Certificate, Email Services - On-demand: Content updates, feature additions, and third-party service adjustments - Our quotes will clearly indicate which category each service falls under and who is responsible for the fees. - Who owns the source code, account, and data? The delivered content includes the complete source code. For domain names, hosting, Google Analytics, and Search Console accounts, we set them up under the client's name initially, and we work as collaborators. This means that when the collaboration ends, you don't need to "retrieve" anything – the website, data, and historical measurements are already yours. When transferring to a new vendor or returning to self-management, only the permissions are transferred, not the assets. - How are common add-on items priced? The base price corresponds to the basic scope. The following are the most commonly added items, each with a separate listing of the cost and work involved, and not presented as an afterthought: - Payment gateway integration (e.g., Green, Blue New, LINE Pay) - Logistics integration and shipping rules - Multi-language versions and language switching - Member system and permission levels - Customization of booking, scheduling, or form processes - Importing and formatting existing data - How are revisions and acceptance documented in the quote? The most common disputes in development projects are not about price, but about "how much should be considered complete." Our quotes clearly state: design confirmation before development, the maximum number of revisions for each stage, acceptance criteria (feature lists and browser ranges), and how additional costs are calculated for exceeding the scope. These terms are not intended to protect the client, but to ensure that both parties have the same definition of "completion" before starting work. - What can a TWD 20,000 corporate website include? Custom design, responsive interface, CMS backend, basic SEO deployment, and contact forms for 5–10 pages. Suitable for websites primarily focused on introducing the company and its services; e-commerce, membership, or custom process solutions fall under the other two schemes. - How is post-launch maintenance priced? Pricing based on the scope of maintenance: maintaining only the host and security updates, or including content updates and feature adjustments, has different prices. The quote will list the items included and excluded in the maintenance, or you can choose to not sign a maintenance agreement and pay per instance. - Can payments or development be phased? Yes. A common approach is to pay in three stages: signing the contract, confirming the design, and launching. For large systems, multiple stages are quoted and accepted separately, with the core functionality launched first, followed by gradual expansion. - Will redesigning a website be cheaper than just having one already? Not necessarily. Redesigning involves tasks like content auditing, data migration, and site restructuring, which a new website wouldn't require. If the existing website's structure is still sound, the associated costs will be reflected in the quote. Conversely, if there's a significant amount of technical debt, rebuilding might be more cost-effective. - Corporate website 20,000 Project start - Custom design for 5–10 - Responsive interface - CMS backend - Basic SEO implementation - Contact Form Corporate website, professional services, and personal branding - E-commerce platform 45,000 Project start - Products and shopping cart - Member and order backend - Payment gateway integration - Logistics integration - Basic SEO implementation E-commerce and D2C - Customized system 75,000 Project start - Requirements and data modeling - Custom process - API and Third-Party Integration - Testing and Deployment - Source Code Delivery Internal Company Systems, SaaS, and Complex Processes ### AI Tool Development Costs | MVP Customer Service, Model Costs, and System Integration Quotes URL: https://www.falconinformation.com/en/pricing/ai-development AI Tool Development Pricing Released: AI Customer Service MVP starting at TWD 30,000, Customized AI Assistant starting at TWD 75,000. This page explains how development costs and model usage fees are calculated separately, the division of knowledge base organization, and the phased pricing structure for MVP to full-scale deployment. AI Customer Service MVP: TWD 30,000 project start-up cost. The AI project costs are divided into two parts: a one-time setup fee and ongoing usage fees for the model. We separate these costs in the quote to ensure transparency and honesty for both parties. - Why are the construction costs and model usage fees listed separately? The setup costs are one-time: this includes dialogue flow design, knowledge base setup, interface and system integration, and testing and delivery. The usage fees are ongoing: each dialogue call requires a language model API, which the platform charges based on usage. Higher usage translates to higher costs, while lower usage results in lower costs. We recommend that these fees be paid directly from the client's API account – pay only for what you use, with transparent billing and no markup from intermediaries. The quotation includes both setup and usage costs, allowing you to accurately calculate your actual monthly operating costs. - Who is responsible for organizing the knowledge base? What percentage of their workload does this represent? Based on our experience with these projects, the effectiveness of AI customer service is approximately 70% dependent on the quality of the knowledge base, rather than the model selection. The knowledge scattered across employee minds, LINE conversations, and old documents needs to be organized into structured Q&A and process documents before the AI can effectively answer questions. This division of responsibilities should be clearly discussed during the quoting process: the client provides the raw materials and domain knowledge, and we are responsible for structuring, deduplication, and testing the coverage. The more disorganized the materials, the greater the effort required for organization, and this will be reflected in the pricing. - What are the key differences between an MVP and a full-fledged product? The TWD 30,000 MVP (Minimum Viable Product) aims to validate: whether AI answers, using a real knowledge base and real customer queries, can meet your desired standards. If the validation is successful, we move on to the next stage, which involves customizing the system for 75,000 users – including integrating with existing enterprise systems, implementing access controls, and transitioning to manual support. If the validation fails, we stop at the MVP stage, minimizing losses. We do not recommend skipping the validation and directly proceeding to the full version, as no one should make promises about performance before the knowledge base has been thoroughly tested. - MVP Phase: Basic conversational interface + small knowledge base + single entry point (website or LINE) - Acceptance criteria: Based on a real-world customer problem and the quality of the solution provided. - Official Version: System Integration, Access Control and Auditing, Manual Handover, and Operational Transition - Each stage can be quoted and inspected independently, allowing you to pause at any point. - Impact of data privacy and deployment options on pricing Most projects utilize cloud-based model APIs, which offer low costs and good quality. However, if your industry has specific requirements for data residency or privacy (such as in healthcare, finance, or government), you will need to evaluate the feasibility of on-premise deployment or data anonymization processes. This will significantly increase the costs associated with setup and maintenance. It is important to discuss these requirements upfront, as they not only affect the price but also the technical direction of the project. - What does an AI-powered customer service MVP with a budget of 30,000 TWD include? Core dialogue interface, small knowledge base setup, website or LINE single-entry integration, testing, and delivery of source code. The purpose is to validate the effectiveness using real data, without involving enterprise system integration or manual phone support. - What is a reasonable estimate for the monthly API costs for a model? This depends on the volume of conversations and the length of the responses. The estimation method is: estimated monthly conversations × average token usage per conversation × model price. We will provide an estimate based on actual usage after the MVP testing, rather than simply quoting a monthly fee. - Should I subscribe to a SaaS customer service tool or outsource development? SaaS is typically faster and cheaper if you don't need to integrate with internal systems. Outsourcing development can be more cost-effective in the long run if you need to integrate with order, inventory, or CRM systems, or if you have custom processes. A detailed cost comparison is available in our article on the cost of implementing AI customer service. - What does maintenance include after launch? Knowledge base updates, quality monitoring of responses, model version adjustments, and bug fixes. Maintenance can be billed monthly or by the hour. The handover includes operation documents, and the client team can take over independently. - MVP for AI Customer Service 30,000 Project start - Basic Conversational Interface - Small Knowledge Base - Single Entry Point on Website or LINE - Testing and Source Code Delivery Validation Process and Use Cases - Customized AI Assistant 75,000 Project start - Custom process - Integration with Company Systems - Permissions and Auditing - Manual Handling Procedures - Handover of Operations Companies with clear process and data integration needs ### SEO Service Costs | Monthly Plans, Scope of Work, and Cancellation Policies URL: https://www.falconinformation.com/en/pricing/seo SEO service fees: Basic plan starting at TWD 7,500/month, Growth plan starting at TWD 15,000/month. This page explains the actual work, contract terms, and exit options corresponding to the monthly fees, as well as the division of responsibilities for content creation. It also outlines situations where we would advise against purchasing a monthly SEO service. SEO Basic Package: Starting at TWD 7,500 per month. The biggest concern with monthly fees is "paying for a service but not knowing what the provider is doing each month" – therefore, this page clearly outlines the specific tasks, delivery schedule, and exit options included in the monthly fee. - What work corresponds to the monthly fee? The pace of the basic plan (starting at 7,500/month): In the first month, we will perform technical checks and measurements and set up the system. After that, we will handle indexing and internal linking issues, prioritize content, and provide a review report at the end of the month. The growth plan (starting at 15,000/month) adds topic clustering planning, case and expert content creation, and competitor gap analysis. The review frequency is bi-weekly. The report includes actual data from GSC and GA4, as well as the next month's work list, not just screenshots. - Contract period and exit options SEO is a cumulative work that usually takes several months to see trends. However, this does not mean you should be locked into a long-term contract. The contract period and early termination conditions will be clearly written in the quotation. More importantly, the exit design: GSC, GA4, and all measurement accounts will be set up on your website and account from day one, and content will be published on your website – when the partnership ends, the rankings, content, and data accumulated will remain with you, not with the vendor. - Division of content production and pricing Effective SEO content requires firsthand experience: actual cases, professional judgment, and industry-specific details. We are responsible for turning these materials into content that can be searched and cited. The division of labor is: you provide interview time or rough drafts (once or twice a month, each lasting about 30 minutes), and we are responsible for selecting topics, rewriting, structuring, and finalizing the content. If you have no time to participate in content creation, we will honestly tell you that the effect of the growth plan will be reduced, and we recommend starting with the basic plan. - When do we recommend not purchasing a monthly SEO fee? Not every website is suitable for starting monthly SEO immediately. If you encounter the following situations, we recommend allocating your budget elsewhere: - The website's structure or speed issues are too significant – a one-time website overhaul is more cost-effective than monthly fixes. - There is no existing content or case studies – first, accumulate actual business results, then there will be content to write about. - The business relies primarily on local customers – first, optimize your Google My Business profile, which is a low-cost and quick way to achieve results. - The budget is lower than the basic package – instead of reducing the scope, first conduct a one-time check and implement it yourself. - What are the differences between the 7,500 and 15,000 packages? The basic package handles technical and indexing issues, provides content prioritization recommendations, and conducts monthly reviews. The growth package includes topic clustering, case study content creation, and competitive analysis, with bi-weekly reviews. Simply put: the basic package focuses on improving the existing situation, while the growth package actively attacks. - How long should the contract be? The contract period and early termination conditions are specified in the quotation. We use a "exit strategy" instead of long-term contracts: your account and content will be under your name from day one, and you can terminate the collaboration at any time, retaining all accumulated assets. - Who provides the content materials? You provide the raw materials (interviews, case studies, expert opinions), and we are responsible for selecting topics, writing, and structuring the content. One to two 30-minute interviews per month are sufficient to generate content. - Does the fee include advertising? No. The SEO monthly fee covers the technical and content work for natural search; advertising (e.g., Google Ads) is a separate service, and the advertising costs are paid directly from your advertising account. - Basic SEO 7,500 Starting from - Technical audit - Index and internal linking correction - Content prioritization - GSC/GA4 measurement - Monthly review Companies with existing websites that require initial basic fixes - SEO growth 15,000 Starting from - Basic plan - Topic clustering - Case studies and expert content - Competitive analysis - Bi-weekly Review Companies needing continuous content and growth in non-branded inquiries ### SEO/GEO Search Growth Costs | Starting Prices and Pricing Factors URL: https://www.falconinformation.com/en/pricing/geo GEO (AI Search Optimization) Pricing: GEO Basic - starting at TWD 12,500/month, Search Growth Integration - starting at TWD 25,000/month. This page explains the differences in monthly fees for GEO and SEO, how to measure results, and what we do not offer. GEO Basic Package: Starting at TWD 12,500/month. The GEO market is full of claims like "guaranteed AI usage" – this page turns that around, explaining the actual work involved, the measurement methods, and what we don't offer. - What do the differences between GEO and SEO monthly fees cover? The differences between GEO basic (TWD 12,500/month starting) and SEO basic (TWD 7,500/month starting) cover three things that are not included in the basic SEO package: one is the AI platform query benchmark – using a set of fixed questions to record the brand mentions on platforms like ChatGPT and Perplexity, creating a repeatable benchmark; two is the physical and author signal – organizing data, real-name authors, and brand consistency on external platforms; three is the evidence-based content – transforming services and case studies into forms with tangible evidence that can be cited. This assumes that the basic SEO package already includes these, as traditional search indexing still relies heavily on AI search. - How to measure effectiveness and what is in the report? The report provides data on five key signals: Search Console Generative AI visibility and presentation pages, Bing AI Performance citations and grounding queries, GA4 AI source and internal behavior, sampled fixed query sets, and qualified queries. Google-specific reports are still being rolled out in phases; Bing citations do not guarantee ranking, authority, or presentation position; and sampled fixed queries are simply samples. All data is presented with caveats and limitations, and does not represent a complete overview of the AI market. - Items We Do Not Offer The following items are commonly promoted in GEO services, but lack official backing; we do not offer: - Guarantees of being cited by ChatGPT, Perplexity, or AI Overview – no guarantee is possible - The so-called "AI-specific schema" – Google does not have this - Promises of seeing results within a few weeks – the pace of AI platform crawling and citation is not controlled by any vendor - Obtaining inclusion through llms.txt – llms.txt is a supplementary file, and Google has explicitly stated that it does not use it - When should you upgrade from SEO to GEO? Upgrade only when both conditions are met. First, your technical SEO and indexing must be healthy: AI search still relies on that index, so GEO lacks a foundation if the basics are broken. Second, you need first-hand material you can publish—real cases, professional perspectives and original data—because AI cites evidence-backed content, rather than marketing copy. If either condition is missing, we recommend staying with SEO to complete the foundations first. That is the more responsible use of your budget. - If I'm already doing SEO, do I need to buy GEO separately? Not necessarily. The GEO solution already includes the basic SEO foundation, and the two are not separate budgets. If your SEO is already being handled effectively by another vendor, you can discuss supplementing with GEO-specific measurement and tracking signals, with the scope and price negotiated separately. - How long does it take to see GEO results? We do not guarantee a fixed timeframe, as the pace of AI platform crawling and citation is not controlled by any vendor. What we can guarantee is honest measurement: each re-tested query set results and citation data will be presented accurately, allowing you to see trends. - How is AI exposure presented in the report? When the account is active, the report includes Google Generative AI impressions and presentation pages, Bing AI Performance citations and grounding queries, as well as GA4 ChatGPT UTM/AI referrer, sampled fixed queries, and query sources. Each item is presented with original data and limitations, and does not represent a complete overview of the AI market. - Do I need to modify my website to do GEO? Usually, yes. Content, structured data, and author information all need to be updated on your website. If your website is not maintained by us, we will first confirm the scope and process that can be modified, and then determine the implementation method. - GEO foundation 12,500 Starting from - Technical SEO and crawler checks - Entity and author data - Content verification - Official AI reports and query benchmarks Companies with existing websites and authentic professional content - Integration of search growth 25,000 Starting from - SEO/GEO fundamentals - Case and original content creation - Digital PR recommendations - Google/Bing AI/GA4 measurement Companies that want to manage both traditional search and AI search ## Comparison page ### SEO, GEO, and AEO: Differences | Discussing Platforms After Building a Foundation URL: https://www.falconinformation.com/en/compare/seo-vs-geo-vs-aeo Google views GEO and AEO as part of search experience optimization. This page compares common names, platforms, and measurement methods, and does not sell special AI Schema without official backing. The industry uses different names to describe AI search work, but the common premise is that the content must be crawlable, indexable, trustworthy, and have value. The names are not three separate budgets. - What problems do the three names address? SEO focuses on enabling websites to be understood, indexed, and compete in search engine results; GEO refers to the industry's use of terms to describe the visibility of brands and content in generative search responses; and AEO focuses on organizing content into writing and information design methods that can directly answer questions. Google does not provide separate channels for GEO or AEO, so these three cannot be packaged as unrelated sets of technologies. - Use Cases and Measurement Methods The same content may appear in general search results, AI Overview, AI Mode, or other AI search platforms, but each platform presents and provides data differently. First, define the decision the user needs to make, and then choose the relevant metrics to observe. Select primary tasks and key metrics based on the user's context - Context - Primary Tasks - Key Metrics - - User search service or comparison vendor - Technical SEO, service pages, case studies, pricing, and conversion paths - Non-brand exposure, clicks, qualified inquiries - - Users asking AI for solutions and recommendations - Indexable content, primary evidence, clear source and brand entities - AI-powered recommendations, case browsing, and lead generation - - Users asking specific and clear questions - Answers, steps, limitations, tables, and relevant internal links - Long-tail queries, cited pages, and follow-up actions - How to prioritize Our recommendations for clients: - Prioritize indexing, speed, website structure, and measurement, as these all affect both traditional and AI search. - Then, invest in real-case studies, author information, original data, and external brand entity signals. - Finally, monitor and generate leads on different platforms, without guaranteeing the effectiveness of the cited phrases. - What phrases should you avoid when purchasing? Claiming that LLMs.txt, FAQPage, HowTo, or the so-called "AI-specific Schema" qualifies for Google's citation guidelines is not in line with Google's official documentation. While structured data can still help describe page entities and support specific search functions, it must be consistent with the page content and cannot guarantee rich results, ranking, or AI citations. - Guarantee AI citation or fixed ranking within a few weeks - Claiming AI exposure growth without specifying the data source - Equating web crawling with guaranteed inclusion or citation - Duplicating the same SEO foundational work into three separate packages - What happens if you only do SEO and not GEO? Google's AI search functionality still relies on search indexes and core ranking systems. Therefore, a strong foundation of technical SEO, content quality, and measurement is essential for GEO. - Does GEO overlap significantly with AEO? There is significant overlap. Falcon views AEO as a design element within a GEO content strategy, and does not offer separate FAQ or HowTo Schema services. - Targeting - SEO - GEO - AEO - Full Name - Search Engine Optimization - Generative Engine Optimization - Answer Engine Optimization - Target Platform - Traditional search engines like Google and Bing - ChatGPT、Claude、Gemini - Perplexity、Google AI Overview - Common Foundation - Crawlability and Indexability - SEO Foundation + First-hand Evidence - Clear Answers + Reliable Sources - Key Metrics - GSC: Non-branded clicks and inquiries - AI Features/Recommendations and Inquiries - Answers, Recommendations, and Inquiries - Specific AI Schema - N/A - N/A - N/A - Falcon Starting Price - 7,500 TWD per month - TWD 12,500 per month - Included in GEO, not sold separately - AI features and your website https://developers.google.com/search/docs/appearance/ai-features Google Search Central 2025-12-10 - Creating helpful, reliable, people-first content https://developers.google.com/search/docs/fundamentals/creating-helpful-content Google Search Central - How are you performing on Google? https://support.google.com/webmasters/answer/10268906 Google Search Console Help ### Comparison of AI Voice and Text-Based Chatbots | Channels, Costs, and Failure Modes URL: https://www.falconinformation.com/en/compare/ai-voice-vs-chatbot Comparison of AI Voice and Text-Based Chatbots on Phone and Website/LINE Channels: Including target audience, cost structure, integration needs, failure modes, and measurement metrics, and explaining the shared backend architecture. The difference between voice and text-based customer service is not a matter of technical superiority, but rather a difference in channels: Do your customers prefer to call, or do they prefer to use LINE and websites? Choosing the wrong channel can prevent even the most advanced AI from connecting with customers. This page compares the cost structures, failure modes, and measurement methods of both. - First, it's important to distinguish: this is about choosing a channel, not about technical superiority. Both approaches share a common underlying process: "understanding the user, gathering information, and executing actions." The difference lies in the entry point. Voice-based customer service exists on the phone: it offers immediate, hands-free interaction, is friendly to older and mobile users, but every second spent on the call incurs a cost, and mistakes require restarting. Text-based chatbots exist on websites and LINE: they allow for detailed responses, the ability to include links and images, and conversations are automatically recorded, but they cannot reach customers who only prefer to call. Therefore, the first and most important question is always: "Where are your customers currently accessing you from?" - What are the key differences in the cost structures? The cost structure of text-based chatbots is relatively straightforward: a one-time setup cost plus API usage fees. Voice-based customer service adds three additional layers: a telecommunications layer (monthly fees and call minutes), a voice recognition and synthesis layer (billing based on audio usage), and a concurrency layer (the number of simultaneous calls determining network and computing resources). This is why our text-based chatbot MVP has a publicly advertised price (TWD 30,000), while voice-based projects insist on assessing the environment first before providing a quote. You rarely see companies offering prices without understanding the specific needs of PBX systems, concurrency requirements, and recording demands. - Different failure modes require different safety net designs. The primary risks associated with text-based robots are related to understanding: misinterpreting intent, model hallucinations, and answering incorrectly – these can be mitigated through the quality of the knowledge base, limitations on responses, and the use of human-in-the-loop mechanisms. In addition to these, voice-based customer service introduces further risks: misidentification, background noise, accents, and call interruptions. Therefore, voice-based processes must include features such as confirmation of key information, escalation to a human agent when confidence is low, and the ability to save the state of the conversation after a disconnection. When evaluating vendors, directly ask "What happens when the system mishears?" and pay close attention to their responses, as vague or idealistic answers are often misleading. - How to choose: Starting with customer behavior, not with technology The approach is practical: review your current customer service records. If a large portion of your interactions are via phone and your customer base prefers verbal communication (e.g., local services, elderly customers), prioritize voice-based solutions; if your interactions primarily occur through LINE and website forms, and your customers prefer text-based responses (e.g., e-commerce, appointment services), prioritize text-based solutions. Start with the channel that handles the largest volume of interactions, validate the process, and then expand to the other channel. When budget is limited, a text-based chatbot is a more accessible starting point, as it eliminates the complexity of voice and telecommunication channels. - Using both: Share the backend, while the interface serves as the entry point. A mature architecture treats voice and text as two entry points within a single system: a shared knowledge base (with maintenance) and a shared backend for actions (processing orders, creating work orders, and transferring tasks through a single API). Voice communication should be concise and conversational, while text can include links. The GoGoCha case study, which we have publicly shared, exemplifies this approach: three entry points – phone, website, and LINE – receive the same backend for order processing. The order of implementation is flexible; the key is to design the backend with multiple channels in mind from the outset, to avoid having to redo it later. - Is it possible to start with text-based customer service, and then add voice support later? Yes, this is a common approach. The knowledge base and backend API can be directly reused, while the addition in the speech phase involves telephone integration and speech processing. The key is to ensure that the backend for the text phase has sufficient expansion space – this should be considered during the initial planning. - Which is more cost-effective: voice or text? Text. Voice adds costs related to telecommunications, speech recognition, and the capacity to handle multiple concurrent calls, and ongoing costs (call minutes and audio processing) are also higher. This is the cost associated with providing a voice channel: some customers only prefer to call. - Can I offer voice customer service on LINE? A common approach is to use LINE for text-based chatbots (which can include voice message recognition), while voice conversations are handled through a telephone channel. Both can be integrated with the same backend, allowing customers to choose their preferred method of communication. - I want to do both. How should the budget be allocated? Start by implementing the channel that serves the largest customer base and validate it, then expand to the second channel. With a shared backend architecture, the incremental cost of the second channel is lower than starting a new project – therefore, the order of implementation affects the risk, not the total cost. - Targeting - AI Voice Chatbot (Phone) - Text-Based Chatbot (Website/LINE) - Interactive Channels - Incoming and outgoing phone calls - Website chat boxes, LINE official accounts - Typical Users - Customers who prefer to call, or those in situations where it is inconvenient to type - Customers who prefer to send messages, and those who can communicate asynchronously - Cost Structure - Development + Telecommunication Line + Speech Recognition + Model Usage - Development + Model Usage (without telecommunication and speech layer) - Integration Needs - PBX/SIP, representative number, recording policy, concurrent capacity - Website or LINE entry, knowledge base, backend API - Main failure modes - Misinterpretation of intent, model hallucination, irrelevant answers - Measurement indicators - Call completion rate, field retrieval rate, human handover rate - Solution rate, conversation flow, human handover rate - Resolution rate, number of dialogue turns, and the rate of manual intervention - Falcon Starting Price - After assessing the needs and the environment, we will provide a quotation. - AI customer service MVP projects from TWD 30,000 ### Comparison of WordPress themes and custom websites: cost structure and maintenance responsibilities URL: https://www.falconinformation.com/en/compare/wordpress-vs-custom-website Comparison of WordPress themes and custom development: cost structure, maintenance responsibilities, scalability, and asset ownership. Let's be upfront: Falcon only offers custom development, but this page will honestly outline scenarios where a theme is more appropriate. Let's be upfront: Falcon offers custom development (using Next.js), but does not offer WordPress theme services. Therefore, this is not a neutral comparison. However, we will honestly outline scenarios where a theme is more appropriate – because if we take on a project that is not suitable for custom development, it will be detrimental to both parties. - Key Differences Between the Two Approaches WordPress is a mature, open-source content management system. The template approach involves building a website using an existing system: selecting a theme, installing plugins, and adjusting settings. Many common needs can be met with readily available solutions. The custom approach involves building from scratch: developing each page, workflow, and backend functionality specifically for your needs. The advantage of the template approach is speed and lower initial cost. The advantage of the custom approach is greater control and long-term flexibility. There is no absolute "better" option; the best choice depends on your specific requirements. - How to Compare Costs Fairly Instead of just looking at the initial cost, consider the total cost over three years. Template approach: Lower initial cost, but you need to factor in annual licensing fees for themes and plugins, hosting costs, and ongoing maintenance (who is responsible for updates?). Custom approach: Higher initial cost, no licensing fees, and maintenance is priced according to the contract. The cheaper option depends on the specifications and the duration of the project – simple branding websites typically have lower overall costs using templates; larger websites with evolving functionality may find that a custom solution becomes more cost-effective over time. Detailed calculation methods can be found in our website pricing article. - Maintenance Responsibility: The Most Often Overlooked Difference This is the most common discrepancy in practice. WordPress's ecosystem is constantly evolving: core versions, plugins, and themes are regularly updated, many of which are related to security. These updates require someone to regularly apply them and handle compatibility issues when they arise. Self-maintenance requires someone to be responsible, while outsourced maintenance involves a monthly fee. Maintenance responsibilities for custom websites are typically assigned to the developer, as outlined in the contract. Both models are viable, provided that you have clearly defined responsibilities before signing the contract: who is responsible for keeping the website healthy over the three-year period? Websites without a clear owner often start experiencing problems in the second year. - When a Template Approach is the Right Choice We would recommend using a template approach in the following situations, even if it means we don't take on the project: The budget is primarily focused on validating the business, and the website only needs standard branding and content functionality; someone on the team is willing to learn how to manage updates; the requirements are highly standardized – such as a blog, event page, and basic forms, where existing ecosystems are already mature. These situations, where customization would add unnecessary expense, are better suited to a template approach. - When Customization is the Right Investment Conversely, customization becomes truly valuable when these signals appear: The business processes are unique (e.g., reservation rules, membership logic, and quotation processes cannot be implemented with existing plugins); deep integration with internal systems or third-party services is required; performance and user experience are key competitive factors (high traffic, e-commerce conversion); the website is a long-term asset that will continue to evolve. The key decision-making factors are: What should this website be able to do in three years? The more specific and less standardized the requirements, the more cost-effective customization becomes. - Transitioning from a Template to Custom: Important Considerations Many clients start with a template approach to validate the business, and then transition to customization as the business grows. This is a perfectly viable approach, but it's important to pay attention to three key things: You should purchase the domain name from the beginning, so you don't get locked out when you switch; the content should be fully exportable (articles, images, and SEO settings); any pages with established search rankings should have corresponding 301 redirects, otherwise, the ranking assets will be lost during the transition. These three things can be confirmed before you even decide to switch – they are also indicators of the health of your current solution. - Can you take over the maintenance of my existing WordPress website? We specialize in custom development and do not offer WordPress maintenance services. If your website needs to be rebuilt, we can assist with the migration planning (content, redirects, and SEO assets). If you only need maintenance for your existing website, we recommend contacting a WordPress-focused agency. - Will a template website have weaker SEO? Not necessarily. SEO performance depends primarily on content quality and technical implementation. Both approaches can achieve good results and can also lead to poor results. The difference lies in the level of control: Customization provides more direct control over speed, structured data, and rendering. Template websites rely on the quality of the themes and plugins. Judging by "who is implementing" is more accurate than judging by "what system is being used." - Will a website migrated from WordPress lose its rankings? Proper redirection is usually manageable: Create a 301 redirect table listing the old and new URLs, preserve the content of pages that retain rankings, and monitor the indexing status using GSC after launch. The biggest risk is failing to create redirects or significantly reducing content – the migration plan should be established during the quotation phase, not after launch. - Can a custom website be maintained after delivery? Yes. We provide the complete source code and deployment documents, with the account registered under the client's name. The client's team can maintain the system independently, or they can outsource it on a per-project basis if needed. This provides the advantage of asset ownership for customized solutions, and the terms of handover can be clearly specified in the contract. - Targeting - WordPress themes - Custom development - Initial cost structure - Lower; includes one-time or annual licensing for themes and plugins - Higher; one-time development costs, no licensing fees - Delivery speed - Fast, days to weeks - Slower, weeks to months - Content editing - Mature backend ecosystem, abundant learning resources - Backend customized according to needs, scope defined upfront - Feature expansion - Primarily using pre-built components, with custom development as a supplement - Direct development, free from the constraints of third-party frameworks - Maintenance responsibility - Continuous management required for core, plugins, and themes - Maintenance responsibility falls on the developer, as specified in the contract - Performance and security control - Depends on the quality and maintenance discipline of the themes and plugins - The entire technology stack is controllable, with responsibility concentrated on the developer - Asset ownership - Content can be exported; licensing of themes and plugins according to terms - Complete source code delivered, account created under the client's name - Falcon Starting Price - This service is not provided - Corporate website projects from TWD 20,000 - WordPress.org https://wordpress.org/ WordPress Foundation ## Content articles ### What is AI-powered voice customer service? Enterprise implementation architecture and suitable scenarios URL: https://www.falconinformation.com/en/blog/ai-voice-customer-service-guide Understand the full architecture, suitable tasks, risks and acceptance process of AI voice customer service, from telephony, speech recognition and dialogue to enterprise API calls and human handoff. AI voice customer service is a software process that can recognize speech, understand tasks, respond to users, and interact with CRM, ticketing, scheduling, or dispatch systems. It's not a single model or simply plugging a website chatbot into a microphone. Its functionality depends on the integration of phone connectivity, field validation, business rules, system actions, and human intervention. - What are the layers of an AI voice customer service system? A complete architecture has at least five layers: telephony, voice, dialogue, workflow and enterprise systems. Telephony handles main numbers, PBX, SIP and transfers; voice handles recognition and synthesis; dialogue identifies intent and asks follow-up questions; workflow validates fields, permissions and state. Only then do API calls create tickets, bookings, CRM records or dispatch requests. Demonstrating natural conversation alone does not establish that the remaining four layers run reliably. Responsibility breakdown from incoming call to enterprise system actions - Hierarchy - Primary responsibilities - Essential validation points - - Phone and routing - Call centers, PBX/SIP, queuing, transfers, and overflow - Peak call volume, dropped calls, human intervention, and number retention - - Voice and conversation - Speech recognition, synthesis, intent detection, and clarification - Handling accents, noise, jargon, and low confidence - - Workflow - Field verification, permissions, rules, status, and duplicate requests - Insufficient data, user misinterpretation, idempotency, and timeouts - - Enterprise System - CRM, service tickets, appointments, dispatch, or notifications - Creation, querying, cancellation, failure reporting, and manual follow-up - Which phone tasks are best suited for initial AI implementation? Prioritize tasks that are highly repetitive, have clear fields, and have verifiable results, and also have a way to recover after errors: - Service status, business information, and case progress inquiries - Create service tickets after collecting address, equipment, and time-slot data - Create appointment, cancellation, or rescheduling requests based on clear rules - Create dispatch, logistics, or in-home service tasks - Pass the processed content to a human for further processing - Which scenarios should not be handled by AI in the first phase? Medical diagnoses, legal conclusions, payment authorization, identity disputes, major customer complaints, and irreversible high-value transactions should not be automated first. Even with voice transcription, these scenarios should be verified by a human before execution. The key is not whether the AI can answer correctly, but whether it can detect, stop, and correct errors. - How to handle AI misinterpretations or system failures? Important fields should be re-confirmed by the user, followed by backend format and business rule validation. When there are continuous misunderstandings, lack of confidence, sensitive keywords, or user requests, the system should hand over the confirmed fields and conversation summary to a human. If the enterprise API times out, it should enter a retry, queue, or pending state, and should not immediately report the task as completed to the user. - Define the boundaries for recordings, transcripts, and personal data Phone processes may involve names, phone numbers, addresses, orders, and call content. Before implementation, the enterprise should confirm the notification method, collection purpose, access roles, retention period, and deletion process. The development team should implement permissions, masking, auditing, and environment isolation. Not all conversations need to be permanently saved, and real customer recordings should not be used directly as untranslated test data. When dealing with specific industry regulations, the enterprise's legal or compliance team should be consulted. - What did GoGoCha demonstrate? The publicly available GoGoCha case demonstrates the integration of AI phone entry, website, and LINE ride-hailing requests into a single real-time dispatch backend, which is then synchronized to the driver/passenger app and operational interface. While the public data demonstrates the system's scope and technical architecture, it does not disclose revenue, labor savings, connection rates, or actual call SLAs. Therefore, we do not include these figures as results. - What acceptance criteria should be defined before the implementation? Don't just test for "conversational ability"; at a minimum, use representative, real-world scenarios to assess it. - Required field completion rate and method of confirmation - Low confidence, sensitive topics, and manual intervention requirements - Task status after API timeout, duplicate requests, and connection loss - Spike merging, waiting, routing, and overflow handling - Information regarding recordings, transcripts, permissions, storage, and deletion. - Are AI voice-based customer service and telephone robots the same thing? These are commonly used in the market. When purchasing, don't just rely on the name; ensure that it can be used to naturally query, call enterprise systems, and validate fields. Also, make sure there's a fallback option to involve a human operator when needed. - Do you need to replace the company's existing phone system first? Not necessarily. Whether or not you can continue using your existing setup depends on factors such as your telecommunications provider, PBX system, SIP, and the method of communication. It's best to conduct a thorough assessment of your current environment before making a decision. - How long will it take for AI-powered voice customer service to be available? Dependent on the environment: Proof-of-concept projects for single-purpose systems are typically billed on a weekly basis, while formal versions including PBX and enterprise system integration are billed monthly. The key variables affecting the timeline are the maturity of the enterprise API and the progress of data consolidation, not the model itself. - Can AI-powered voice assistants handle Taiwanese or multiple languages? The accuracy depends on the extent to which the speech recognition engine supports the specific language and accent. Before implementation, test the recognition rate using recordings from real users, which is more reliable than relying solely on the vendor's specifications. If the initial tests fail, start by limiting the scope of the service. ### Cost of AI-powered voice customer service: setup, phone, model, and maintenance costs URL: https://www.falconinformation.com/en/blog/ai-voice-customer-service-cost AI voice-based customer service does not have a single, fixed price. This article breaks down the costs associated with setup, including telecommunication fees and model usage, system integration, concurrent capacity, human agent availability, and ongoing maintenance costs. AI voice customer service costs usually include one-time design and integration plus ongoing telephony, speech recognition, speech synthesis, model, hosting and maintenance costs. If a vendor gives a seemingly precise total without asking about inbound or outbound calls, peak concurrency, the existing PBX, enterprise API interfaces, recording policy and human agent seats, that figure probably does not cover a production-ready scope. - What work is included in the one-time setup fee? The cost of a customized project typically doesn't involve purchasing a model license, but rather involves transforming a company's processes into a testable and recoverable system. - Phone infrastructure, task, and risk assessment - Dialogue, required fields, confirmation, and manual intervention design. - PBX, SIP, VoIP, or cloud-based phone systems - Integration of CRM, ERP, work order, appointment, or dispatch API - Permissions, logs, error handling, and retry mechanisms, as well as testing and deployment procedures. - What are the costs associated with each month or each phone call? Ongoing costs may include phone numbers and call minutes, speech recognition, speech synthesis, language models, servers, monitoring, recording storage, and vendor maintenance. Different providers have different pricing units, so it's not possible to simply compare the price per minute of a single model. A single phone call may use both telecommunication and speech services, as well as the model service. Quotes should clearly distinguish the actual usage by the third-party vendor from the developer's maintenance fees. The AI phone budget should be broken down into verifiable cost items. - Cost types - Common pricing methods - Information needed before valuation - - Telephone and Wiring - Monthly rental based on the number of calls, minutes, or simultaneous lines. - Incoming calls/outgoing calls, domestic and international, simultaneous - - Audio and Model - Minutes of audio, characters, tokens, or requests - Language, average call duration, task complexity - - Corporate integration - One-time development and testing - PBX, API, permissions, testing environment, and data agreements - - Operations and Maintenance - Monthly fee, hourly rate, or SLA tier - Monitoring, audio recording, seat allocation, shift scheduling, and frequency of changes - Why is a high call volume more important than the average call volume? With an average of 100 calls per day, the volume could be evenly distributed or concentrated in short periods. The latter requires more simultaneous call lines, voice processing capacity, API throughput, and human agent availability. If capacity is only estimated by monthly total minutes, peak periods could still result in queuing or failures. Therefore, it should provide information on peak periods, simultaneous calls, and acceptable wait times, rather than just monthly call volume. - What are the costs that are most easily overlooked? The following items often appear after the initial presentation but are crucial for a successful launch: - Organize and manage specialized terminology, addresses, product information, and knowledge base data. - Modifying or creating an intermediary layer when a system lacks an API. - Human-assisted and seat management processes for individuals with low confidence - Recording, permissions, storage, deletion, and auditing - Continuously monitor for misclassifications, process changes, and supplier anomalies after deployment. - How to obtain a truly comparable quote? Please have all vendors respond to the following questions using the same format: Call direction; Phone number and PBX integration; Simultaneous calls; Language; Tasks; Required fields; Company API; Manual handover; Recording policy; Deployment method; Estimated usage; Maintenance responsibility and acceptance standards If one vendor only provides information about the voice model, while another provides information about phone and system integration, the total costs cannot be directly compared. - What are the key elements to include when writing a valuation scenario for comparison purposes? First, describe a scenario that can be easily verified, such as "successful on-time arrival during peak hours, simultaneous communication with three different lines, collecting data from five required fields, and creating work orders. This also includes handling low-confidence and complaint cases, requiring two manual operator positions." Then, ask the vendor to provide separate quotes for Proof of Concept (POC), full implementation, monthly fixed fees, estimated usage, and overage pricing. This is not a public commitment, but rather a disclosure of the unknown conditions, to avoid discovering that phone calls, recordings, or manual operator positions are not included after the system is launched. - Why hasn't Falcon publicly disclosed the starting price for its AI phone? The typical starting price for chatbots does not necessarily reflect the cost of a complete phone system. A phone system includes telecommunications, real-time communication, call handling, voicemail, and responsibility for call failures. Advertising a low starting price without first assessing the specific needs and environment can mislead businesses into believing that the full range of features is included. Falcon first conducts a needs and environment assessment, then separately lists the costs for setup, third-party usage, and maintenance. - Could we start with a small-scale proof of concept? Yes, and it is recommended to choose only one task with clear rules and the ability to recover from errors. The POC should still include scenarios where the system fails and requires human intervention, and should not only demonstrate successful conversations. - Does the model fee cover all the costs? No. Features such as phone calls, voice recognition, voice synthesis, servers, storage, monitoring, and enterprise integration and maintenance may all incur separate charges. - Are AI-powered voice assistants definitely cheaper than human customer service agents? Not necessarily. The cost-saving advantage of reduced per-call costs is significant when call volume is high and tasks are repetitive. However, if call volume is low or there are many exceptions, the savings in labor may not be enough to offset the initial setup and maintenance costs. It's best to first estimate the potential savings based on your own call volume, and then decide whether or not to proceed. - What items should be included in a quotation to be considered complete? At a minimum, the quotation should clearly separate the costs for: one-time setup, telephone and line usage, voice and model usage, and monthly maintenance fees with overage charges. A single quotation with a total price is insufficient for comparing quotes from different vendors and for verifying the accuracy of the costs. ### How to choose between AI-powered voice customer service, IVR, and human agents? URL: https://www.falconinformation.com/en/blog/ai-voice-vs-ivr-human-agent Compare the advantages and disadvantages of AI-powered voice assistants, traditional key-press IVR systems, and human customer service agents, including their suitability for different tasks, potential error risks, and strategies for hybrid implementation. AI voice-based customer service, traditional IVR, and human agents are not mutually exclusive. Simple, low-risk tasks with limited branching can be handled by IVR; tasks requiring natural language understanding and repetitive system operation can be handled by AI; and human agents remain the primary option for tasks involving emotions, exceptions, significant stakes, or irreversible decisions. Most companies are better suited to a hybrid approach. - Advantages and Limitations of Traditional IVR IVR uses key presses or pre-recorded voice menus to route calls, making the rules clear, the results predictable, and the system risks easily manageable. It is suitable for short processes such as call routing, department selection, and entering fixed codes. However, the drawback is that with many branches, it can become difficult to navigate, and users may still need to be transferred to a human operator if they don't know which option to choose. Don't replace existing, reliable IVR systems with AI just because it's new. - What types of customer service inquiries are well-suited for AI voice assistants? The advantages of AI include its ability to understand more natural language, ask clarifying questions when information is missing, and translate results into actions within an enterprise system. It is well-suited for collecting repetitive but varied data, creating cases, querying status, and assigning tasks. However, its limitations include the potential for misinterpretation by both speech recognition and the model. Therefore, it is essential to use field verification, backend rules, and human intervention to limit errors to a manageable level. - Which jobs should still be performed by humans? Significant customer complaints, emotional support, contract and legal disputes, medical assessments, payment authorization, identification of anomalies, and cross-departmental exception handling all require understanding the context, taking responsibility, and exercising flexible judgment. While AI can organize existing data, search for records, or create to-do lists, it should not pretend to have complete decision-making authority. - In practice, a hybrid architecture is more stable. A common division of labor is not "AI replacing humans," but rather assigning each layer to handle the aspects it is best suited for: - IVR: Handles the most common routing, identity verification, and required disclosures. - AI: Capable of processing natural language, asking clarifying questions, organizing data, and performing low-risk system actions. - Real-life scenarios: Handling exceptions, sensitive decisions, customer complaints, and conversations with individuals who lack confidence. - Backend: Standardized authentication, data format, retry mechanisms, status management, and auditing. Choose between IVR, AI, human agents, or a hybrid approach based on the specific requirements of the task. - Assessment direction - IVR - AI voice customer service - Live customer service - - Input method - Buttons or fixed options - Natural language and multi-turn questioning - Natural language understanding and flexible reasoning - - Suitable for the task - Extension, number, short-range call routing - Data collection, searching, and operation of low-risk systems - Customer complaints, exceptions, sensitive or high-stakes decisions - - Key Risks - The menu is too deep, and I can't find the option I'm looking for. - Identifying and correcting misclassifications and errors in models - Waiting time, human resources capacity, and consistency - - Essential safety net - The ability to switch personnel at any time. - Field verification, backend validation, and handling low confidence scenarios. - Knowledge, skills, records, and management support - What questions should be answered before choosing a business? If you are unable to answer the following questions, please refrain from selecting a supplier or model just yet: - What is the most common task that callers are typically asked to complete? - Which fields are incorrect and can be corrected, and which fields are absolutely essential to be correct? - What is the maximum time allowed for multiple openings and acceptance of applications? - Which enterprise systems and permissions does the AI need to access? - When transitioning between different roles or projects, what context information should be provided? - What is the GoGoCha business model? GoGoCha's key focus in its public implementation is to integrate car-hailing requests from phone, website, and LINE into a shared backend, rather than simply creating a voice-based chat interface. This architecture retains human intervention, utilizing the app, backend, and real-time notifications to manage task status, aligning with the hybrid approach of "AI handles repetitive entries, backend controls tasks, and humans handle exceptions." - In what situations would it be more reasonable to implement only IVR or only add human agents? If the primary need is simply to route calls by department, input fixed numbers, or play pre-recorded messages, then IVR systems are often more cost-effective and predictable. If call volume is low but each call involves complex customer complaints, negotiations, or professional judgment, then improving the human agent experience, knowledge base, and CRM interface may be more effective. The value of AI should come from automating repetitive tasks and integrating with existing systems, rather than simply appearing in purchasing presentations. - Is AI always better than IVR? Not necessarily. Fixed routing systems using IVR are typically simpler and more controllable. AI only offers significant value when dealing with natural language and multi-turn questioning. - Are customer service agents still needed after implementing AI? Typically, this role involves handling routine tasks, but with a focus on resolving exceptions, sensitive issues, and high-value conversations. The handover process should be completed and verified before taking over the role. - Can I use both my existing IVR and AI systems simultaneously? Yes, and this is often the most reliable approach: IVR retains legal disclosures and fixed routing, while AI handles natural language processing tasks, both utilizing the same backend and human agent resources. There's no need to replace the entire IVR system just to introduce AI. ### How to integrate AI phone with PBX, CRM, ticketing, and dispatch systems URL: https://www.falconinformation.com/en/blog/ai-phone-pbx-crm-integration This involves disassembling the AI phone system, including its telephony layer, dialogue layer, workflow, and integration with enterprise systems, encompassing PBX/SIP, data contracts, error handling and retry mechanisms, and manual handover. AI phone integration is not simply a matter of using a single API. The telephony layer handles number, routing, and call forwarding; the dialogue layer converts speech into structured data fields; the workflow layer verifies permissions, rules, and status; and finally, CRM, ticketing, scheduling, or dispatch systems are responsible for the actual business actions. If these four layers are not clearly separated, a failure in any one layer could lead to duplicate orders or incorrect commitments. - What are the roles of PBX, SIP, and AI respectively? PBX management includes call distribution, routing, and call queuing/transferring; SIP is a common voice communication protocol; and AI handles recognition, understanding, and response. Whether a company can continue using existing phone numbers depends on the telecommunications provider, the PBX's capabilities, and existing contracts. AI vendors cannot simply state that they "support SIP" and assume that all requirements for numbers, recordings, transfers, and concurrent calls are already met. - The conversation content needs to be converted into a data agreement first. Corporate systems should not directly receive complete natural language sentences, but rather define the necessary fields, formats, sources, confirmation status, and unique request identifiers. For example, a repair order might require fields such as equipment, address, contact information, service hours, and problem category. AI can only suggest potential values, but these values must be confirmed and validated by the user and the backend system before being executed. - What should be checked in the CRM, work order, and dispatch API? Before connecting, please ensure the following interface conditions are met: - Are there any official APIs, a testing environment, and a permission model? - Responsibilities for establishing, querying, updating, and canceling - How to avoid duplicate case creation from the same call - Is it possible to inquire about the final status when a request is overdue? - Can an event or webhook be used to retrieve the subsequent status? - When the API request times out, the AI cannot initially report a successful response. While a delayed response online doesn't necessarily mean a task has failed, nor does it guarantee success. The system should use unique identification, idempotent processing, a retry queue, and status queries to prevent duplicate orders. If the result cannot be confirmed during the call, it should clearly inform the user that the request has been transferred to a pending status and establish a manual follow-up or subsequent notification, rather than simply responding with "completed" to maintain a smooth conversation. - What contextual information needs to be manually transferred? The transcript should at least include fields for call source, confirmed information, unresolved issues, conversation summary, system query results, and reasons for failure. Whether the original recording or transcript is provided to the assigned representative depends on the notification, authorization, and retention policies. If only the call is transferred without any context, the user will still need to repeat the entire conversation, which would diminish the value of automation. - How should a POC (Proof of Concept) be validated? Choose a specific business task and test it in a realistic phone environment using API validation. Verify that the process works smoothly, that there is sufficient data, that there are no identification errors, that duplicate requests are handled correctly, that API timeouts are handled properly, that the enterprise system rejects invalid requests, that users are correctly identified, and that manual intervention is handled appropriately. The results of the testing should allow you to track each step of the process from the backend, rather than just listening to a pre-recorded ideal conversation. - Key integration points for GoGoCha GoGoCha utilizes a modular architecture based on Express, PostgreSQL, Redis, BullMQ, and Socket.IO to integrate phone calls, websites, and LINE into a single dispatch workflow. The database stores task status, while the queue handles asynchronous tasks, and real-time communication synchronizes data to the app and operational interface. This case demonstrates that cross-channel workflows don't necessarily translate directly to all businesses using PBX systems. - Can older systems without APIs still be integrated? Each system should be evaluated individually. It may be necessary to first implement APIs or intermediary layers for older systems; direct manipulation of the user interface through automation is inherently less reliable and should not be treated as equivalent to a formal API. - Does establishing a SIP connection automatically mean that an AI-powered telephone system is complete? No. SIP only handles a portion of the voice transmission, and further steps are still required, including dialogue, data verification, actions within enterprise systems, monitoring, fallback procedures, and manual intervention. - Which system permissions should be granted to the developer during the integration process? The principle is to apply the principle of least privilege: test environments should have full administrator access, while production environments should only have access to the necessary API ranges, and all actions should be logged for auditing purposes. If a client requests full administrator access before starting work, this should be treated as a warning sign and clarified before proceeding. ### How to validate an AI-powered voice customer service proof of concept? Test scenarios, metrics, and go-live criteria URL: https://www.falconinformation.com/en/blog/ai-voice-agent-poc-acceptance-checklist Use representative conversations, the "golden test" case, and failure scenarios to evaluate the AI voice customer service system, checking for task completion, misunderstandings, correct field values, API execution, latency, and handover to human agents. The purpose of the AI voice customer service proof-of-concept (POC) is not to demonstrate a successful demo, but rather to answer three key questions within a limited scope: can a real incoming call successfully complete the designated task; if the call fails, can it be detected and handled; and is the overall cost justified for full implementation? The POC only verifies the naturalness of the voice or the smoothness of the conversation; it cannot prove that the system can correctly create work orders, check status, or protect important data. - First, break down the Proof of Concept into a manageable business task. The POC (Proof of Concept) should focus on tasks that have relatively clear rules, predictable call volumes, results that can be verified in the backend, and can be corrected if errors occur. For example, creating a work order after collecting repair data is more suitable for verification than "handling all customer service issues." Before starting, it's important to clearly define the call entry points, required fields, executable actions, prohibited actions, handover conditions, and which entity provides the company API and testing environment. If the scope cannot be clearly defined, the verification process will simply become a subjective assessment. - First, establish a baseline for the existing manual processes, and then discuss how AI can improve them. Without a baseline, it's impossible to determine whether the POC (Proof of Concept) has improved. At a minimum, record who currently handles the task, how success is defined, common errors, peak wait times, and any data that needs to be re-entered. The baseline doesn't necessarily need to be a polished KPI; a small number of verified actual cases are preferable to assumptions made by the vendor. When comparing, use the same tasks, similar incoming conditions, and consistent definitions of success. - The gold test cases should include scenarios for normal, ambiguous, and failed paths. Initially, the business, customer service, and system personnel would jointly create the input, expected follow-up questions, necessary fields, allowed actions, and final states. This would then be submitted to the system for repeated testing. The test cases should not rely solely on verbatim readings; they should include variations in user speech, missing data, homophones, background noise, silence, interruptions, API timeouts, and requests for human interaction. When dealing with names, addresses, amounts, or identification information, it is also important to test whether the AI will rephrase and confirm, rather than simply comparing the output to the original text. Minimum Test Matrix for AI Voice Customer Service Proof of Concept (POC) - Context - What to observe - Verifiable results - - Completed successfully - Required fields, question order, and tool calls - CRM/Work Order/Assignment Status must match the call record. - - The information is unclear or inaccurate. - Did you re-confirm and overwrite the old value? - Only keep the final confirmed data, and do not create duplicate orders. - - Misunderstanding of speech - Low self-confidence, repetitive questioning, and reliance on manual processes - The error was not directly written into the official system. - - API timeout or rejection - Reply, Retry, Pending, and Idempotency - Do not announce success prematurely; the final state should be trackable afterward. - - Requests for human interaction or high-risk activities - The routing protocol establishes a connection with the appropriate network based on the context. - Fields marked as "Confirmed" and unresolved issues have been manually reviewed. - The metrics should be aligned with the tasks, and not just focused on accuracy rates. Accurate speech recognition does not guarantee task completion. Errors in the transcript do not necessarily affect the outcome. Acceptance should consider task completion, the accuracy of required fields, successful tool calls, misunderstandings or fallback scenarios, planned handoffs, abnormal upgrades, user abandonment, response delays, and the amount of manual correction. Each factor should have a clear denominator and data source, for example, using "successful test calls within the defined range" as the denominator, and verifying this through phone records, model events, API logs, and the final state of the enterprise system. Focusing on the acceptance criteria for both conversation quality and system results. - Indicator - Definition - Avoiding Misinterpretations - - Task completion rate - The percentage of calls that fall within the defined range and have the correct final status. - A conversation alone does not constitute the completion of a work order. - - Accuracy of required fields - The degree to which the verified fields match the actual answers. - The average value cannot obscure key fields such as address and amount. - - Tool executed successfully. - The API call was successful and produced no duplicate or erroneous side effects. - Online transactions cannot be directly classified as either successful or unsuccessful due to the possibility of delays. - - Misunderstandings and fallback mechanisms - The system is unable to understand or process the frequency of repeated questions. - Distinguish between reasonable questioning and unproductive repetition. - - Manual handover - Planned transfers, unexpected upgrades, and user-initiated requests - Not all instances of outsourcing are failures; they need to be categorized based on the reasons for the failure. - The threshold for launching a project must be set according to the estimated cost. There is no single passing line that applies to all AI phone systems. The costs associated with incorrect operating hours and modifying payment details are entirely different; even a single typo in an address can be more problematic than unnatural phrasing. The approach is to first categorize the errors into three categories: those that can be automatically retried, those that require manual review, and those that cannot be automatically executed. Then, set different thresholds and assign responsibility for each category. If the sample size is insufficient, we can only say that the POC has not yet identified specific issues, and we cannot conclude that the system will definitely meet the standards in a production environment. - The acceptance testing process should also include verifying the system's ability to function correctly after a failure. Formal services will inevitably encounter issues such as network outages, timeouts, API errors, full call center lines, and vendor maintenance. During the POC, it is crucial to verify how each type of issue is handled, where the data is placed during the outage, who receives notifications, and whether it is safe to retry after the issue is resolved. The front-end and operational back-end must clearly display understandable error messages, without swallowing exceptions and leading customer service to believe that the issue has been resolved. - GoGoCha can serve as evidence in a structured manner, rather than being a general acceptance data. GoGoCha has publicly demonstrated Falcon's capabilities in AI-powered phone entry, shared order backend, queuing, real-time notifications, and integration with websites, LINE, apps, and back-end systems. However, the case study did not disclose specific metrics such as recognition rate, average latency, connection rate, or cost savings, nor did it provide formal service level agreements (SLAs). Therefore, these figures cannot be used to set benchmarks for other companies. The new proof of concept still requires re-validation using the target company's phone environment, customer language, and task data. - What deliverables should be produced before a Proof of Concept (POC) is ready for release to a full version? At a minimum, the following should be documented: fixed test cases, detailed results, unresolved risks, system architecture, data flow, permissions, monitoring, manual intervention and recovery procedures. The final version should also include peak load testing, real PBX/SIP testing, redundancy testing, recording policies, and operational permissions. The POC should only indicate that further development is worthwhile, not that the system can be directly deployed and operated without further testing or adjustments. - How many calls are needed to conduct a Proof of Concept (POC) for AI-powered voice customer service? There is no universal number. The sample must cover the main intentions, common phrases, important failure paths, and different call conditions; high-risk or low-frequency exceptions cannot be determined by chance; instead, specific test cases must be deliberately created. - Can POC (Proof of Concept) be tested using only a web microphone? It can be used for preliminary verification of communication, but it cannot replace a real phone call verification. A formal POC should include actual phone routing, audio quality, call forwarding, and integration with enterprise systems to avoid issues such as telecommunication delays, dropped calls, and PBX limitations. - Does a high number of manual transfers necessarily indicate a failed POC (Proof of Concept)? Not necessarily. A planned transition for high-risk situations could be the correct approach. It's important to distinguish between planned transitions, transitions initiated by users, and unexpected upgrades caused by system errors. - Evaluate agents with golden test cases and scenarios https://docs.cloud.google.com/gemini-enterprise-cx/cx-agent-studio/evaluation Google Cloud Documentation - Voice virtual agent dashboard metrics https://docs.cloud.google.com/contact-center/ccai-platform/docs/voice-virtual-agent-dashboard Google Cloud Documentation 2026-08-26 ### How to measure and address AI voice assistant delays and interruptions? VAD, Barge-in, and Hand-off design. URL: https://www.falconinformation.com/en/blog/ai-voice-latency-barge-in-turn-taking This document breaks down the components of AI voice customer service, including telecommunications, VAD (Voice Activity Detection), models, and latency, and explains how to test for features such as interruptions, errors, silence, noise, and p50/p95 test methods. The AI voice customer service can sound choppy, and the reason may not always be the model itself. Delays can occur due to factors such as network connectivity, voice activity detection, turn-taking, model inference, and the use of enterprise APIs and voice synthesis. Speeding up one particular aspect may also lead to the interruption of the user's incomplete speech. The correct way to measure performance is not just to record the "response time," but to observe the delays, interruptions, and the final outcome of the task together. - Where does the waiting time for an AI phone call come from? After the call passes through the telecommunications and SIP/PBX routing, the audio is processed, and the system determines whether the user has finished speaking, it then uses a model to understand the call and initiate a request to the enterprise tool. Finally, the response is converted back into audio and sent back to the phone. If querying a CRM or creating a ticket requires waiting, the perceived latency will also be affected. Only measuring the initial token of the model will ignore the entire path that the caller actually experiences. End-to-end latency analysis for AI-powered voice customer service - Stage - Measurement start and end - Common Risks - - Telephone transmission - Incoming and outgoing audio communication platform - Electrical routing, encoding/decoding, network jitter, and packet loss - - Boundary identification - The system will stop processing once the user has finished speaking. - Waiting too long or cutting it off prematurely - - Sample Response - Submit valid input to generate playable content. - Long context, model selection, and complex reasoning. - - Call for tools - Send an API request to retrieve available results. - Enterprise System Timeout, Retry, and Queuing - - Audio playback - The text or audio begins to play on the phone. - Synthetic buffering, initial package waiting, and playback cancellation - VAD addresses the question of "whether someone is speaking," while contour detection focuses on "whether the speech is complete." Server-side VADs typically determine the start and stop of speech based on volume and silence duration. Semantic VADs go further by estimating whether the meaning is still in progress. Longer waiting times reduce the risk of cutting off speech, but also increase the duration of pauses. If the VAD reacts too quickly, it may cut off phrases like "um... I want to change that" into two separate segments. The parameters cannot be universally applied; names, addresses, codes, and open-ended descriptions require different levels of tolerance for pauses. - "Barge-in" refers to interrupting a conversation, and it does not necessarily mean that the conversation is over. "Barge-in" allows the caller to interrupt the AI during playback and stop the original response, which is useful for correcting information, skipping known content, and shortening menus. However, "Barge-in" and the system's silent judgment of the user having finished speaking are two separate things. Generally, interruptions should be allowed during normal conversations; however, recording prompts, necessary disclosures, or important field confirmations should be handled according to individual company processes and legal requirements. Turning "Barge-in" off globally will make conversations feel unnatural, while turning it on globally could prevent important content from being played. - Don't just report the average latency; also look at the p50, p95, and error rates. The average value can be easily skewed by a small number of very slow or very fast samples. The p50 value represents the typical response time, while the p95 value represents the worst-case scenario that is still commonly encountered. Additionally, the data records the time it takes for a user to stop speaking and receive the first response, the time it takes for the tool to complete, the occurrence of errors, the time spent waiting for errors, and the failure of interruptions. Each sample must also be labeled with the task, network, language, and whether an API call was made to the company. Without this information, it is difficult to pinpoint the cause of the problem when different scenarios are mixed together. The delay and rotation should be recorded together. - Observation project - Definition of an event - Determining the purpose - - Initial response delay - Confirm that the process has ended when the user hears a response. - Differentiating between sequential, model-based, and synthetic waiting - - Tool is waiting. - The API has successfully retrieved the data and it is now available for use. - Identify bottlenecks in corporate systems or third-party services. - - Truncated error - The user started responding before they had finished speaking. - Adjust VAD, row, and column strategies. - - Error waiting - The user has finished speaking, but the system remains silent. - Check completion status, timeout, and tool status - - The comment was successfully posted. - Once a user makes a comment, the original response is stopped, and the new input is retained. - Verify that the playback is consistent with the context. - The real-world phone test should include elements such as background noise, echo, accents, and long pauses. The microphone on a webpage, when tested in a quiet office setting, cannot be assumed to function correctly on mobile phones, in cars, with hands-free devices, Bluetooth headsets, or landlines. The test should cover a range of scenarios, including background noise, echo, signal instability, varying speech speeds, common accents, numbers, alphanumeric codes, and long addresses. The goal for critical fields is not just to ensure accurate transcription, but also to ensure that the system can re-transcribe, allow the user to correct errors, and stop processing if the accuracy is uncertain. - When a tool call goes unanswered for a long time, avoid filling the silence with false assurances. CRM, ERP, or dispatch API requests may take several seconds or even initiate asynchronous processes. While the system can use brief status updates to avoid a completely silent experience, it cannot say "completed" before the results are returned. When the expected conversation time is exceeded, it should transition to a "pending confirmation" or "manual processing" status, and use a unique identifier to prevent redundant execution. If optimizing for speed sacrifices the accuracy of the results, it simply makes the error more obvious. - "3 seconds" can only be a design goal, not a Service Level Agreement (SLA) that GoGoCha publicly commits to. GoGoCha's publicly available case studies demonstrate the effectiveness of the phone-based entry and real-time dispatch workflow, but they do not provide publicly available data on end-to-end latency distribution, telecommunications environment, call samples, or Service Level Agreements (SLAs). Product design goals should not be written as achieved service levels without the same event definition and real measurements. Companies should re-establish p50, p95, and failure sample data within their own PBX/SIP, API, and peak conditions. - Is it essential for AI-powered voice assistants to have responses that are less than one second in length to sound natural? Not all tasks require the same amount of time. Quick questions and tasks that require accessing company systems differ from those that simply involve waiting; the user experience is also affected by factors such as the length of the wait, whether the user is interrupted, and whether the progress and results are accurately reported. - Which is better, Server-side VAD or Semantic VAD? The choice between Server VAD and Semantic VAD depends on the level of support and the type of call. Server VAD is easier to control with silence parameters, while Semantic VAD can wait for the meaning to be fully processed, but this may introduce latency. It's best to compare the two options based on your specific needs, including the language, fields, and call samples you use. - Why is the website demo running smoothly, but the phone call is slow? In reality, the number of actual phone lines, along with their routing, encoding, network quality, and PBX configurations, can vary significantly. Therefore, the POC (Proof of Concept) must be tested using the specific phone paths that are intended for actual use. - Realtime API reference: SIP and voice activity detection https://platform.openai.com/docs/api-reference/realtime OpenAI Platform Documentation - Agentic voice best practices: barge-in and end-of-turn tuning https://docs.aws.amazon.com/connect/latest/adminguide/agentic-voice-best-practices.html Amazon Web Services Documentation ### How are AI-powered phone recordings and personal data handled? This includes information on notification, storage, permissions, and an audit checklist. URL: https://www.falconinformation.com/en/blog/ai-call-recording-privacy-security Compile a list of AI-powered call recording, transcription, field, and model data, and organize and collect information related to disclosure, retention, deletion, minimum access rights, vendor information, and proof-of-concept (POC) testing data. AI phone calls leave behind more than just one audio file. Transcripts, caller ID, call summaries, model event data, API fields, manual annotations, and backups can all contain identifiable information. If companies only discuss whether or not to record calls without assessing the flow of data, the purpose of collection, access roles, retention periods, and deletion procedures, risks can be scattered across the phone provider, AI vendor, company systems, and testing environments. This article provides a technical and governance assessment, not legal advice. - What information would be recorded in a phone call? The recording is just one part of the data chain. The call number, call duration, SIP identification, transcript, summary, sentiment/intent tags, name and address, CRM query results, tool call parameters, customer service notes, monitoring events, and backups should all be included in the inventory. Each item should be marked with who created it, where it was sent, who can view it, how long it is stored, and how it is deleted. If the vendor cannot provide answers, simply stating that the data is encrypted is not sufficient. AI Phone Data Inventory - Data type - Common Locations - Main Issues - - Original audio - Telecommunications companies, voice platforms, and audio storage. - Is it necessary to inform, obtain consent, retain, and download? - - Full transcript and summary - Model platform, application backend, and customer service interface - Ability to identify content, erroneous content, and search permissions. - - Structured fields - CRM, work order, appointment, or dispatch system - Objectives, accuracy, minimal fields, and correction - - Model and Tool Events - Supplier log, monitoring, and auditing platform - Information on prompts, API parameters, retention periods, and cross-border transactions. - - Backup and Export - Object storage, backup, and customer service download files - After the main system is deleted, can it still be restored or scattered? - Recordings of individuals, whether obtained directly or indirectly, may be subject to regulations under data protection laws. The Ministry of Justice's interpretation states that recordings from customer service lines that can directly or indirectly identify specific individuals may constitute personal data, and their collection, processing, and use are subject to the Personal Data Protection Act. In practice, the content of phone calls is often linked to the caller's phone number, name, order details, address, or membership information. Therefore, it is not possible to assume complete anonymity simply because the recording does not contain a name. Whether the data can be identified and which legal provisions apply still depends on the judgment of the company's legal department based on the actual procedures. - Before recording, confirm the purpose and legal basis for the recording. Companies should first determine who is collecting the data, the purpose of collection, the scope of use, the retention period, the recipient of the data, and the rights of the individual, and then decide on the method of notification during the call. It is not appropriate to assume that all recordings require the same form of consent, nor to assume that existing customer service protocols automatically cover AI models, transcripts, and third-party vendors. Industries such as finance, healthcare, telecommunications, and outsourcing may have specific industry regulations, which should be verified by legal or compliance personnel. - The shelf life should be determined based on the intended use, and should not be assumed to be permanent. Recordings may require different durations and permissions for dispute resolution, quality control, model improvement, or legal preservation. Each purpose should be determined separately, and after the expiration of the term, the original file, transcript, summary, exported files, and backups should be permanently deleted or made unrecoverable. If the system only allows for adding data but not querying or deleting, it cannot guarantee that the company can fulfill its own preservation policies. Save and delete inspection checklists - Checkpoints - Inspection issues - Evidence that should be preserved - - Intended Use and Duration - What is the purpose of preserving each piece of data, and for how long? - Approval policies and system settings - - Query and Access - Who can find the relevant information based on the case or the parties involved? - Role-based access control and query auditing - - Delete and unrecognize - What to do after an application has expired or been approved? - Delete event, outcome, and exception lists - - Backup and Export - When do copies expire, and how can I manage downloaded files? - Backup frequency and export records - The principle of least privilege should apply to individuals, service accounts, and model tools. Customer service representatives may only need to view summaries and confirmed fields, while supervisors can access the recordings. Developers and suppliers should not obtain all official data solely for ease of maintenance. The API calls should be limited to necessary actions, with important writes requiring backend verification. API keys should not appear in conversations or the frontend. Each view, export, deletion, and permission change should leave an audit trail, and the frontend should fully display any operation failures. - Evaluating suppliers shouldn't just focus on whether a model can be trained using existing data. It is also important to verify the data processing location, the responsible party, default storage and deletion methods, access for personnel, encryption, event notifications, export and clearing after service termination, and whether different environments are isolated. Telecom providers, voice recognition, models, and monitoring systems may be provided by different companies. Any identifiable data left behind must be included in the contract and data flow. Supplier policies may change over time, so it is important to keep the current version and review it regularly before formally deploying the system. - POCs should not directly upload unisolated audio recordings into the testing environment. Prioritize the use of artificially generated, anonymized, or properly authorized test data. If real samples are necessary, they should be limited in scope, access restricted, set to expire, and usage documented. Personal information such as names, phone numbers, addresses, medical records, payment details, and account information should be masked according to risk levels. After testing is complete, ensure that supplier logs, downloaded files, and backups are also handled appropriately, and that only the application database is not deleted. - The incident response process should clearly identify the layer where the data is stored. When data is misdirected, improperly exported, or due to authorization errors or vendor issues, organizations need to quickly verify the affected data, time, user, vendor, and subsequent flow. Monitoring systems should not require personal information like names, phone numbers, or complete transcripts for convenience; error codes, event identification, and security summaries are usually sufficient for pinpointing the problem. Incident reporting, evidence preservation, and handling of involved parties should be determined by the organization according to applicable laws and internal procedures. - Is it always necessary to obtain consent before recording phone calls using AI? It cannot be generalized. Whether consent is required, what legal basis is needed for collection, and the content of the notification, all depend on the purpose, the relationship between parties, industry standards, and the actual process. This should be confirmed by the company's legal department, not solely based on answers from the system provider. - If I don't keep the recordings, but only the transcripts, would that avoid any privacy issues? Not necessarily. Literal transcripts, abstracts, phone numbers, and structured fields can still directly or indirectly identify individuals, and should be included in the data inventory and policies regarding access, storage, and deletion. - Does hashing a phone number make it anonymous? Not necessarily. If the same algorithm can still be used for comparison, linking with other data, or re-identification, the data may still be considered personal data. The assessment of anonymization should focus on the overall level of identifiability, not just the individual fields. - Interpretation of the Customer Service Hotline Call Recording and Personal Data Protection Act https://mojlaw.moj.gov.tw/LawContentExShow.aspx?etype=etype5&id=FE253692&kw=&type=E Ministry of Justice 2012-11-22 - Comprehensive Guide to Industry Best Practices for Personal Data Protection and Management https://www.ncc.gov.tw/chinese/files/21033/5164_45874_210331_2.pdf National Communications Commission 2021-03 - Even information that cannot be directly identified may still be subject to the interpretation of the data protection law. https://www.pdpc.gov.tw/News_Content/102/1056/ Office of the Personal Data Protection Committee 2025 ### How to transition from AI voice customer service to human agents: Trigger conditions, context handover, and fallback mechanisms. URL: https://www.falconinformation.com/en/blog/ai-voice-human-handoff-escalation Explain when to transition AI voice customer service to a human agent, how to transfer context through PBX/SIP/call queues, and how to handle degraded performance during full call, disconnection, and system failure scenarios. AI-powered voice customer service doesn't rely on a "failure button" for transferring calls; instead, it's an integral part of the complete service process. The system should first determine when it's appropriate to transfer, identify the correct agent, gather all relevant information, and leave a clear next step for the agent to follow, whether the call is busy, disconnected, or if there's an issue with the company's system. Simply transferring the call back to the main switchboard and having the caller repeat everything doesn't constitute a proper handover of context. - First, let's define the conditions under which AI must be stopped. Users can be assigned based on clear requests for human intervention, instances of continuous miscommunication, inability to verify required fields, involvement of financial transactions or sensitive information, high-risk keywords, API responses indicating an error status, or abnormal behavior of models or phone services. The criteria should be defined as recordable reason codes, rather than relying solely on the model's own judgment. This allows customer service representatives to understand the reason for the call, and also enables the operations team to identify issues related to process design or model quality. Manual intervention and expected handling - Causes - Things AI should do - Key takeaways from the presentation - - Users require a human operator. - Please confirm your details and join the appropriate queue immediately. - Status: Identity confirmed and awaiting further instructions. - - Recurring misunderstandings or lack of confidence - Stop guessing and explain the purpose of the adapter. - Original problem, failure field, and number of times re-asked - - Sensitive or high-risk matters - Do not perform irreversible actions. - Risk classification and related case data - - Corporate system failure - Do not claim success; instead, maintain a state of pending completion. - API status, request identification, and retryability - - Artificial seating is not available. - Offer options for queuing, calling back, or creating tasks. - Contact information, hours, and tracking identification - It is important to measure the impact of both planned upgrades and unexpected surges separately. The planned transfer is designed to be handled by humans, such as AI collecting data and then passing it to a specific agent. An escalation occurs when the AI is unable to understand, the system fails, or the user is dissatisfied. When these two situations occur together, the team may mistakenly believe that all transfers to humans are failures of automation, and it may also obscure the true underlying problem. Google Cloud's virtual customer service metrics also distinguish between planned transfers, escalations, resolved cases, and abandoned cases. - PBX, SIP, and call queuing systems are responsible for the actual routing of phone calls. AI applications can propose routing goals and reasons, but features like call forwarding, call transfer, group calls, operating hours, queueing, overflow handling, and voicemail are typically managed by PBX systems, SIP platforms, or contact centers. Before implementing, it's crucial to verify features like blind transfer, consultation transfer, keeping the original number, cross-system call identification, and handling failed transfer scenarios. Simply stating "supports SIP" is not sufficient to demonstrate that the existing phone system can handle all routing requirements. - The handover will only include the necessary materials required to complete the assigned task. The system should at least require the user to provide the purpose of the call, information already confirmed, unresolved issues, results of queries to corporate systems, actions taken, and the reasons for failure. Whether the original recording, complete transcript, or sensitive fields are displayed should be determined based on the user's role and purpose. If the work can be completed using summaries and essential fields, all data should not be exposed. The screen should also clearly indicate which values the user needs to confirm and which are simply model predictions. Suggested minimum handover content - Data - Applications - Control methods - - Reason code for connection - Prioritize tasks and determine the next steps. - Use fixed categories to prevent the model from generating arbitrary commands. - - Confirmed fields - Prevent users from answering the same questions repeatedly. - Confirmation time and source information - - Unresolved issues - Enable the system to directly continue the conversation. - Present the model summary separately from the main text. - - System Status - Avoid redundant queries or creating duplicate entries. - Includes unique request identifier and final status. - - Safety Summary - Quickly grasp the context. - The mask obscures personal information and restricts access to the original text. - Regardless of whether the connection is successful, fails, or is interrupted, there must be a next step. If all seats are occupied, users can choose to wait, request a callback at a specific time, or create a support ticket. If the API call fails, the original call should be retained, retried to a backup queue, or clearly explain the next steps. Before attempting to call back after a disconnection, it's important to verify the purpose of the call, the validity of the number, and company policies. Each fallback path should generate a case ID and display a visible status on the front-end, and errors should not be logged for the user to manually re-enter. - Evaluating the effectiveness of manual intervention requires considering both the reasons and the outcomes. The transfer rate can only indicate the extent to which requests are routed to manual intervention. It cannot be used in isolation to determine whether a process is good or bad. It should be considered in conjunction with other metrics, such as the number of planned transfers, the frequency of abnormal escalations, misrouting, requests abandoned due to queuing, the first resolution rate, the total processing time, and the proportion of user explanations. If a particular intent results in a high number of planned transfers, it may indicate that the process design is correct. However, if a specific field consistently causes abnormal escalations, it signals that the dialogue, data, or model needs to be revised. - GoGoCha has not provided any public evidence of its complete call center transfer capabilities. GoGoCha's publicly available content demonstrates the integration of a phone entry system, a shared dispatch backend, real-time notifications, and integration with websites, LINE, apps, and operational interfaces. However, it does not disclose information about specific PBX models, call queue management skills, full-line strategies, or transfer SLAs. This information, which Falcon can customize for specific business environments and validate through a proof-of-concept, cannot be packaged as a complete and validated customer service solution as demonstrated by GoGoCha. - Users are asking: Should the AI continue to try to persuade the person to stay, or should it give up? It is generally not advisable to design systems that repeatedly block access. While it is acceptable to request necessary routing information once, users should be directed to an alternative option or transferred according to established protocols if they repeatedly request human assistance. - Is a complete, verbatim transcript required after the adaptation? Not necessarily. For many tasks, it's sufficient to provide the reason for the transfer, confirmed fields, unresolved issues, and a summary of the key points; a complete transcript or recording should only be provided when necessary, based on the purpose, relevant permissions, and data privacy policies. - Is it possible to implement AI-powered phone support without a dedicated customer service area? While it can be evaluated, it's crucial to design alternative fallback procedures, such as creating work orders, assigning specific callback times, or transferring tasks to on-call personnel. If a high-risk task cannot be handled by humans, AI should not be allowed to perform it automatically. - Voice virtual agent dashboard: planned transfer, escalation and abandonment https://docs.cloud.google.com/contact-center/ccai-platform/docs/voice-virtual-agent-dashboard Google Cloud Documentation 2026-08-26 - Voice agent design best practices https://docs.cloud.google.com/dialogflow/cx/docs/concept/voice-agent-design Google Cloud Documentation ### GEO Generative Engine Optimization Guide: How to Prepare Your Technical and Content Assets URL: https://www.falconinformation.com/en/blog/geo-complete-guide-2026 Based on Google's official guidelines for 2026, this presentation covers GEO (Google's Entity, Relationship, and Opinion) from various sources, including search indexes, original content, real-world examples, AI crawlers, and measurement techniques. It also clarifies common misconceptions about LLMs (Large Language Models) and their associated schemas. GEO is the industry-standard term for AI search visibility, not a set of mysterious codes. Google's official guidance in 2026 clearly states that AI Overview and AI Mode do not require any additional technical barriers, and Google does not use llms.txt. What truly matters for long-term accumulation are search indexes, original content, verified identity, external trust, and conversion measurement. - The Common Ground and Differences Between GEO and SEO Google's generative search functionality is built on top of its search index and core quality system, so GEO does not replace SEO. According to Google's official documentation, pages that can be used in AI Overview or AI Mode must first be indexed and meet the general search snippet requirements. There is no additional technical application required. The key differences lie in the context and measurement: SEO typically focuses on non-branded queries, natural clicks, and informational searches; while GEO focuses on AI-driven recommendations, the appearance of established question sets, and whether the brand is accurately described. - The first step is not to write more, but to ensure that the content can be easily scraped and indexed. First, check the robots.txt file, CDN/WAF settings, HTTP status, canonical URLs, noindex tags, internal links, and sitemap. Important information must be present in easily accessible HTML, and should not be restricted to images, login pages, or interactive elements that search engines cannot access. Technical requirements are simply a prerequisite for participation, and do not guarantee that a page will be indexed or cited. If the page itself does not clearly answer the question, adding a dedicated AI file will not fill the content gap. - The second step is to establish a verifiable value for a single hand. AI-powered searches make it easy to consolidate existing knowledge online, so businesses need to clearly state "what they have done, how they know, and any limitations." Falcon achieves this by linking service descriptions, identified authors, public case studies, technical diagrams, and limitations. It does not extrapolate benefits from operational data without customer consent, and it does not claim to replicate verified results. This approach not only improves human decision-making, but also benefits AI systems. - The examples illustrate the actual scope of responsibility, data sources, time frame, and any confidential or non-public projects. - The article is written by named authors, clearly distinguishing between official rules, project experience, and personal opinions. - The document includes the source and diameter of the product, but the target performance level (SLA) is not specified as having been achieved. - Create internal links between service pages, articles, case studies, and the "About" section to establish a traceable chain of evidence. - The third step is to create topic clusters based on the identified problems. Avoid creating numerous pages with similar content based on individual keywords or city/industry-specific terms. The core service page should address procurement and delivery, the guide page should explain the principles, the cost page should cover the budget, and the case study page should demonstrate practical application. Each page should have a distinct primary question and next step, and these should be linked using descriptive anchor text. If two pages address the same topic, they should be merged or re-organized rather than each being expanded to around 2,000 words. - What can structured data do, and what can't it do? Structured data such as Organization, Website, Service, Article, and Breadcrumb can help describe the page's entities, and the content must align with the text that users can see. Google explicitly states that AI features do not require specific Schema; proper tagging only indicates eligibility to use the corresponding search functionality, and does not guarantee rich results, ranking, or citations. If there is no physical store, "LocalBusiness" will not be outputted; if there are no publicly available reviews, "AggregateRating" will not be automatically filled in. - How can we accurately measure GEO data, rather than simply reporting on screenshots? First, establish a baseline before publishing, then cross-validate using official reports, on-site behavior, and business results. Google has launched a Generative AI performance report for Search Console, which allows users to view data on AI Overviews and AI Mode, including impressions, display pages, countries, devices, and dates. However, this feature is currently only available to a limited number of websites. Bing Webmaster Tools also offers AI Performance data, including citation counts, cited pages, and grounding queries. However, these numbers do not represent rankings, authority, or position within search results. When official reports are not available, revert to standard web performance metrics, GA4, fixed query sets, and query sources. Avoid packaging sampling data as overall platform exposure. Recommended measurement levels for GEO - Hierarchy - Observation project - Interpreting limitations - - Availability - Crawling, indexing, canonicalization, and accessing AI-powered web crawlers - This does not necessarily imply a ranking or citation. - - Google AI Visibility - Generative AI: Exposing, displaying, and identifying the page, country, device, and date. - The reports are still released in batches, and they are not ranking reports. - - Bing AI citations - Citations, cited pages, grounding queries, and trend analysis - The number of citations does not indicate ranking, authority, or presentation position. - - AI-powered recommendations - Behavioral data from sources like ChatGPT and Perplexity - Lack of explicit mentions and app-specific privacy restrictions may lead to underestimation of data. - - Business results - Demo, forms, phone calls, and qualified inquiries - To eliminate the influence of other activities and seasonal variations. - Common Misconceptions about GEO Google does not require llms.txt, AI text files, or specific markup to access AI Overview/AI Mode. Structured data is also not a requirement for AI indexing. The ability for crawlers to access a platform does not guarantee that its content will be indexed. The timing of when content is indexed is not fixed, as it depends on factors such as search queries, competition, and the indexing status of the platform and its models. The key indicators of successful indexing are technical availability, content evidence, and the ability to find and request information, rather than the vendor's promised timeline. - Do GEO and SEO conflict with each other? They are mutually reinforcing. Technical SEO, original content, clear sourcing, and brand trust all form the foundation for both traditional search and AI search. - Can I do this myself? First, ensure the page is indexable, add original authors and case studies, and establish benchmarks in GSC/GA4. If there is no original content, prioritize gathering firsthand experience, as this is more important than adding more tags. - Is GEO something that needs to be done every month? Technical maintenance is phased, but content updates and measurements are ongoing: cases need to be regularly reviewed and updated, query sets need to be re-tested periodically, and new content needs to be continuously added. A one-time check can identify problems, while long-term visibility is achieved through continuous maintenance. - Optimizing your website for generative AI features on Google Search https://developers.google.com/search/docs/fundamentals/ai-optimization-guide Google Search Central 2026-07-10 - Creating helpful, reliable, people-first content https://developers.google.com/search/docs/fundamentals/creating-helpful-content Google Search Central - Generative AI performance report (Search) https://support.google.com/webmasters/answer/16984139 Google Search Console Help - Introducing AI Performance in Bing Webmaster Tools Public Preview https://blogs.bing.com/webmaster/February-2026/Introducing-AI-Performance-in-Bing-Webmaster-Tools-Public-Preview Microsoft Bing Webmaster Blog 2026-02-10 ### Schema.org Structured Data Tutorial | JSON-LD, Validation, and Common Errors URL: https://www.falconinformation.com/en/blog/schema-org-tutorial Schema.org is used to describe page elements and supports specific search functions. This article explains the types of schemas, those that are deprecated, and the rules for content consistency. Schema.org provides a structured format for websites to define the entities they contain, allowing search engines to understand the content more clearly. However, it does not guarantee ranking or serve as a prerequisite for AI-powered search. Accuracy and relevance are more important than quantity; the markup must be visible on the webpage. - First, clearly distinguish between Schema.org and Google Search functionality. Schema.org provides a set of common vocabularies for describing entities and relationships. Google only supports a subset of these types as the basis for specific search results. Websites can use valid Schema.org properties, but this does not guarantee that Google will display rich results. Before deploying, it's important to verify that the page's primary content, Google's support for the relevant functionality, and the availability of sufficient, accurate data for marking. - What types of content are actually used on this website? Falcon uses a concise and consistent `@graph` definition, allowing brands, websites, authors, and page content to share a single set of entity identifiers. - Organization: Brand Identity and Public Contact Information - Website: The relationship between the website and its publisher. - Service: Clearly defined scope of services and the provider - Article: Content of the article (including author and publication date) - BreadcrumbList: Breadcrumb Navigation - Profile Page/Person: Real-name authors and publicly verifiable professional affiliations - Creative Work: Case Content and Evidence Revealed - How should JSON-LD be deployed? Google recommends JSON-LD, and also supports Microdata and RDFa. Next.js can include the `application/ld+json` script within the HTML generated on the server. The key is that the data should be easily crawlable, the JSON should be parsable, the URL should use a canonical version, and each field should be verified against the main content or relevant information on the page. Shared entities should use stable `@id` values to avoid creating multiple, conflicting entities on the same page. - Establish the schema order based on the content of the image. Instead of first finding a template generator and then filling it with content, a safer approach is: - The primary purpose of the confirmation page, along with the concept of canonical URLs and their relationship to visible content. - Choose types that are supported by Google and are relevant to the main content. - Only maps existing author, date, image, service, or case study data. - Use the Rich Results Test to check Google functionality, and use the Schema Markup Validator to check general syntax. - After the website goes live, use URL Inspection to verify the actual HTML that Google is retrieving. - Common Mistakes - Avoid using fabricated aggregate ratings (such as a self-assigned rating of 4.9 stars out of 50 reviews) – this violates Google's Rich Results policy. - If the schema content doesn't match the actual content on the page, Google will directly reject the rich results. - While lacking a physical storefront, the business can display its LocalBusiness address or operating hours. - Commercial websites use FAQ pages, HowTo sections, and AI-powered response generators as standard rich results or AI reference shortcuts. - Why can't FAQ, HowTo, and Speakable be mixed together? It is evident that the FAQ section still holds value for users, but Google's FAQ rich results are primarily limited to authoritative government and health websites. The "HowTo" rich result is no longer displayed. Speakable's Google document feature is also limited to specific news contexts. This does not mean that websites cannot use Q&A or step-by-step content, but rather that they should not make promises to general businesses that they will automatically receive rich results or AI citations simply by adding relevant tags. - Passing the test does not necessarily guarantee that it will be displayed. Rich Results Test: While Google may display a page based solely on its adherence to technical specifications and certain criteria, the final decision on whether to display rich results depends on the search context, quality policies, and the page's overall relevance. If structured data is misleading, hides content, or violates policies, the page may lose its rich result eligibility, and in severe cases, may be flagged for manual review in Search Console. This does not necessarily mean that the page's organic ranking will decline, but it can significantly diminish the value of incorrect or misleading markup. - Will incorrect schema definitions result in penalties? Structured data that is misleading or violates policies may lose its eligibility for rich results and could also be subject to manual review. Common risks include providing fabricated AggregateRatings, marking content that is not visible to users, and creating fictitious business or author entities. - JSON-LD, Microdata, and RDFa: Which one should I choose? Google supports all three formats. The official recommendation is JSON-LD: separating it from the HTML, making it easy to maintain, and preventing layout issues. If an existing system already uses Microdata extensively, it's best to continue using it. However, for new projects, directly adopting JSON-LD is recommended. - Do structured data formats require each page to contain all the information? Determine the type of page based on its content: "Organization" and "Website" can be used across the entire site, "Article" pages should have the "Article" tag, and "Service" pages should have the "Service" tag. Avoid forcing irrelevant tags onto pages – it's worse to have no tag than to have the wrong one. - General structured data guidelines https://developers.google.com/search/docs/appearance/structured-data/sd-policies Google Search Central - Google Search structured data markup https://developers.google.com/search/docs/appearance/structured-data/search-gallery Google Search Central - Changes to HowTo and FAQ rich results https://developers.google.com/search/blog/2023/08/howto-faq-changes Google Search Central Blog ### The reasoning behind Perplexity AI's approach and its practical implementation in AEO. URL: https://www.falconinformation.com/en/blog/perplexity-aeo-overview Perplexity will list the sources used. This article only uses official scraping rules and reproducible measurements, and does not claim any fixed citation formulas that cannot be verified. Perplexity's responses typically include links to sources, but citing a source does not guarantee traffic or conversions. Official documents can confirm the intended use and access methods for web crawlers, but there is no publicly available formula that websites can use to guarantee that their content will be cited. Websites should first ensure that their public content is accessible to search crawlers, and then improve their content using authentic sources, primary evidence, and reproducible measurements. - PerplexityBot is different from Perplexity-User. Perplexity officially distinguishes between two user agents: PerplexityBot, which is used to build a search index and display website links, and is not used for training the underlying model; and Perplexity-User, which accesses pages in real-time when a user poses a question. The former follows the robots.txt protocol, while the latter is a user request, and official documentation states that it is generally not subject to robots.txt control. If a website uses a WAF, it is also necessary to verify both the user agent and IP range published by Perplexity, to prevent allowing unauthorized crawlers based solely on the user agent name. Official uses of Perplexity's web crawler - User agent - Applications - Important notes for visitors - - PerplexityBot - Create a search index and display links in the results. - The robots.txt file allows crawling, and the WAF verifies against the official IP address. - - Perplexity-User - Access the page when responding to user questions. - Manage separately from index crawlers, and control access based on website security policies. - The ability to be "caught" is merely a starting point, not a guarantee of success. The following conditions can be verified by the platform itself, and also contribute to improved search results and readability for general users: - Page returned 200, canonical tag is correct, and important content is present in accessible HTML. - The topic should be specific, include the names of the authors, date, source, and firsthand experience. - The title and paragraphs directly answer the question, but do not aim for a fixed word count for the benefit of third-party scoring systems. - The update date reflects the actual modification time, and is not fabricated each time the system is deployed. - Unlike other websites, this content offers specific, actionable examples, methods, or limitations that can be directly applied, rather than simply providing a summary of existing information. - What tasks should be performed by the content team? Falcon treats "answering first" as an editorial method, rather than a Perplexity official ranking factor. It begins by providing a concise answer to the topic, followed by evidence, steps, comparisons, and limitations, allowing human reviewers to quickly assess the applicability of the information. External sources should link to the original documents, while internal experience should link back to case studies or relevant personnel pages, and clearly indicate which are implemented and which are merely suggestions. - Provide clear and concise answers to the questions, and then include any relevant conditions or exceptions. - Enhance verifiability through publicly available case studies, original data, and official documents. - Obtain natural mentions from real customers, partners, or professional communities. - Use real author names, stable brand names, and consistent company information. - Update the page date and sitemap time only when the content is substantially changed. - How to measure Perplexity? First, observe perplexity.ai's referrals, landing page interactions, and queries within GA4 or server logs. Then, use a fixed set of questions, closely aligned with customer decision-making, to manually check the sources regularly. Avoid only measuring brand names, as this only reflects existing knowledge. Also, avoid relying solely on screenshots to claim rankings, as answers may change over time, depending on location, the model used, and the way the question is phrased. If the platform doesn't include links, analysis tools often cannot fully capture brand mentions. - Does allowing Perplexity to equal a certain value imply agreement with the model training process? According to Perplexity's official documentation, PerplexityBot is used for indexing search results, not for pre-training AI base models. This only reflects the company's currently disclosed use of web crawlers, and does not imply that websites can ignore their own content licensing, privacy, and access policies. Paths containing customer data, paid content, or internal information should still be protected with logins, permissions, and server controls, and should not rely solely on robots.txt. - Is Perplexity's citation logic the same as that of ChatGPT? These should not be considered the same set of rules. The indexing, query processing, response generation, and source presentation methods vary across platforms, and they are all subject to updates. However, the underlying principle remains the same: publicly accessible, topic-relevant content with clear sources and original value, and the effectiveness of each platform should be measured separately. - Should I block PerplexityBot? Based on your goals: If you want to achieve AI search visibility, allow scraping; if there are paid content or licensing concerns, block it, and combine it with server-side access control. This is a policy decision that can be adjusted at any time. Our site's choice is to be fully open and regularly review access logs. - How much traffic can be generated by citing Perplexity? Due to variations in queries and industries, there is no reliable, fixed number. Instead, use GA4 to observe the actual number of users referred by perplexity.ai and their subsequent actions, and use your own data to determine the value. Do not rely on average figures provided by third-party sources. - Perplexity Crawlers https://docs.perplexity.ai/docs/resources/perplexity-crawlers Perplexity Documentation - How does Perplexity follow robots.txt? https://www.perplexity.ai/help-center/en/articles/10354969-how-does-perplexity-follow-robots-txt Perplexity Help Center 2026-07-16 ### What is Google AI Overview? And how does it affect SEO? URL: https://www.falconinformation.com/en/blog/google-ai-overview-basics Google AI Overview: This article provides an overview of how Google's AI generates answers directly on search result pages. It also discusses the impact of this on traditional SEO and how to adjust content strategies accordingly. The Google AI Overview feature will organize information and provide supporting links in certain searches. AI Mode is better suited for more complex exploration, comparison, and in-depth research. The platform does not have a dedicated submission form or specific schema; pages must first meet the general technical and content requirements of Google Search. Instead of guessing how each page will change, it's more practical to ensure that the content is indexable, has value, and that search and conversion results can be tracked. - AI Overview and AI Mode: How to use them on the webpage? Google's official explanation states that these two features may use "query fan-out," breaking down a complex question into multiple related searches and finding relevant support pages. Because different features may use different models and methods, the displayed answers and links will vary. The "AI Overview" feature only appears when the system determines that it can add value to a general search, and it is not triggered by every query. This also means that a single "target keyword" is not sufficient to cover the subtopics that users may explore. - What are the basic requirements for a website? To become a supported link for "AI Overview" or "AI Mode," the page must be indexed by Google, display a summary in Google Search, and comply with Google's search technology and policy requirements. Google does not have any additional requirements for AI technology and does not require the addition of new AI text files or a dedicated schema. However, meeting these requirements does not guarantee that the page will be crawled, indexed, or displayed by Google, as Google's results are determined by its query and quality systems. - robots.txt, CDN, and WAF allow Googlebot to crawl - The page should be indexable, have a correct canonical URL, and display a search summary. - Key information is presented in text format and can be accessed through links within the site. - The structured data aligns with the content that users can see and understand. - The page design, images, and videos genuinely aid in understanding when appropriate. - What factors increase the chances of your content being selected as a source? Google does not publish a fixed citation formula, but the principle of human-centered content still applies: directly answering questions, providing project experience, citing original sources, and clearly indicating the author and any limitations. Tables and lists can improve understanding, but they are not special ranking signals. The real difference lies in whether the information is more specific and easier to verify than existing results. If an article simply restates existing definitions, even if it is lengthy, it does not add any new value. - Common reasons for failure The following issues simultaneously reduce the usability of both general search and AI-powered search: - Pure marketing jargon (lacking verifiable information) - The key is buried very deep (it needs to be slid all the way to the bottom to appear). - Content that requires JavaScript to be rendered - Repeating basic internet knowledge without firsthand experience or unique value. - How much AI-related data can I see in Search Console? Google has launched a standalone Generative AI performance report for Search Console, which displays website visibility and presentation in AI Overviews and AI Mode, including metrics such as page views, countries, devices, and dates. This report is currently available to a limited number of websites and does not provide data on clicks, CTR, or average ranking. The relevant exposure data is still included in the standard Web Performance report. If you haven't seen the dedicated report, you should not use third-party sampling to estimate Google's overall platform exposure based on trends in non-branded searches and landing page performance in Web Performance, combined with GA4 conversion data. Division of labor after publication - Source of information - Suitable for answering - It cannot be proven in isolation. - - Generative AI reports - AI features revealed, display pages, country, device, and date. - Queries, clicks, CTR (click-through rate), ranking, or websites that are not yet open. - - Web Performance - Non-branded searches, landing page performance, click-through rates (CTR), and overall trends - Was each exposure generated by the AI function? - - GA4 / Analytics Tools - Do users read the case studies, click on the call-to-action buttons, or inquire after arriving at the station? - Mentions of brands without any clicks - - Practice Problems - Does the specific problem originate from the description of the product or brand? - Overall market visibility or fixed ranking - Do not draw conclusions based on limited or unreliable data. AI Overview may allow some users to directly obtain answers, or it may provide new support links for complex issues. The results from a single website are affected by the query combination, brand, layout, competition, and time, and cannot be directly stated that traffic will definitely decrease or that "getting clicks through citations will guarantee results" without having its own Search Console and conversion data. The correct approach is to establish benchmarks based on page-specific and non-branded queries, and then observe the trends after the changes. - Will AI take my website traffic? It's important not to make generalizations. Different searches and websites may yield different results; instead, use your own Search Console data for clicks, impressions, and click-through rates, and compare them to your own inquiry benchmarks, rather than relying on average figures or guarantees from third-party sources. - AI Overview: When will AI appear in search results? According to Google's search query analysis, the results are only displayed when the system determines that they add value to the search. The website cannot proactively trigger these results. Therefore, when analyzing trends, it's important to look at the overall trend rather than just taking a single snapshot, as the same query may yield different results at different times and in different locations. - Should I create a separate version of the AI Overview content? No. The links for the AI Overview come from a general search index, and the page must meet the general search criteria. Maintaining two separate sets of content is much more practical than having one page with both the question and the answer. - Optimizing your website for generative AI features on Google Search https://developers.google.com/search/docs/fundamentals/ai-optimization-guide Google Search Central 2026-07-10 - Generative AI performance report (Search) https://support.google.com/webmasters/answer/16984139 Google Search Console Help ### 2026 Taiwan Website Development Costs | Pricing Range, Hidden Costs, and Quotation Comparison URL: https://www.falconinformation.com/en/blog/website-pricing-2026 Website development can cost tens of thousands to several million TWD. What explains the difference? This article examines four price bands, commonly overlooked hidden costs and what to check when changing vendors. The cost of website development varies greatly. This article only discusses "what the actual costs include," how to interpret quotes, and how to calculate total costs over three years, without disparaging any specific vendor or tool. - Four price ranges for setting up a website in Taiwan Price ranges overlap because the determining factor is not the word "website" itself, but the specifications: the number of pages and processes, whether the design is template-based or custom, the level of backend management required, and whether to integrate with payment gateways or external systems. The same "company branding website" can have vastly different costs depending on whether you use a template and build it yourself or hire a team to customize it – both approaches are valid, but comparing quotes based on different specifications is the key. The following ranges represent a rough estimate based on our experience and observations of the industry; actual costs will vary depending on the specific specifications: - TWD 3,000-30,000: Template websites (e.g., Wix, Squarespace) – Suitable for individuals and small businesses - TWD 30,000-100,000: WordPress pre-built templates or semi-customized solutions - TWD 100,000-500,000: Full custom development - TWD 500,000+: Complex systems / Large e-commerce / Multi-language enterprise websites - Hidden costs that are often overlooked In a quotation, you'll typically only see a line item for "setup fees," but a website is a continuously generated asset that requires ongoing costs. Before signing any contract, it's important to clarify the following details: "Who pays, who receives the payment, and how much is the annual fee." This will help avoid discovering budget shortfalls after the website is launched. Pay particular attention to licensing fees: some themes, plugins, and image libraries are billed annually. The initial year's cost may be included in the setup fees, but from the second year onwards, it will become your ongoing expense. - Server/Domain Annual Fee - CMS or plugin licensing fees (especially for commercial WordPress packages) - SSL certificates (most vendors include these, but it's important to verify) - Subsequent maintenance costs (typically billed separately) - Cost of modifications (Does a minor change include the cost? How are major changes calculated? Must be clearly stated in the contract) - Moving/Relocation Costs (Costs associated with changing vendors) - Things to confirm before signing a contract The following questions should be asked before signing the contract, and the answers will be included in the agreement. However, questions asked after signing the contract will be determined by the other party. The two most important items are "ownership of the source code" and "ownership of the main server account," as these determine whether you will be able to take the complete website with you when switching vendors: - Who owns the source code (This should be clearly stated in the contract, otherwise, you will be in a passive position when changing vendors) - Is the primary account under your name or managed by the vendor? - Is it possible for me to make changes to the CMS backend myself? - To what extent is SEO integrated (using Lighthouse SEO scores as a benchmark)? - Does it support responsive design? - Warranty coverage and duration after purchase - A Breakdown of Common Items on Quotation Forms Quotes from different vendors vary greatly, so here's a breakdown of common terms in plain language: "Visual Design": Is this simply tweaking an existing template, or starting from scratch with wireframes? The workload difference is significant, and the quote should clearly state which approach is being used. "Frontend Development / Backend Development": Frontend refers to turning design drafts into webpages, while backend refers to the unseen logic of user accounts, forms, and admin panels. Only websites with simple image-based pages have a low backend development percentage. Complex websites with integrated functionality require a much larger backend development effort. "CMS Backend": This refers to the interface that allows you to modify content. It's important to clarify the scope of changes (just text, or also layout and new pages?). "SEO Basic Setup": This typically includes meta tags, sitemaps, robots, structured data, and basic speed optimization. Be wary of quotes that guarantee rankings, as this is often unrealistic. "Project Management Fee": This is not just for "padding" the price. It covers tasks such as requirement gathering, progress coordination, and final documentation. However, the percentage is usually between 10% and 20% of the total project cost. If you don't understand a term, ask for a detailed explanation. A reputable team will be able to clarify. - When should a website be redesigned, and when should it simply be updated? Not every "outdated website" needs a complete overhaul. The key is to identify the root cause: is the content outdated, are the images old, or is the design causing issues? If the problem lies in the content, simply updating it is sufficient. If the issue is with the design, a minor redesign may be enough. However, if the problem is at the technical level – if the backend is no longer used, if adding new features is impossible due to the existing system, if the original code is unavailable, or if the website building tool is no longer supported – then attempting to fix it will only lead to further costs without providing any real benefit. Another common time to rebuild is when the business model changes. If the website was originally only for showcasing a brand, but now needs to handle online orders, this is a fundamental change that requires a new website. Before rebuilding, it's important to inventory the assets of the old website: pages that need a 301 redirect, content that needs to be migrated. These tasks should be included in the quote. - When evaluating a website, it's important to look at its performance over three years, not just the initial price. One of the most common mistakes people make when getting quotes is focusing solely on the initial setup cost. However, websites are ongoing expenses – domain registration, hosting, SSL certificates, content updates, and maintenance all require annual payments. When comparing different plans, it's important to consider both the initial setup cost and the ongoing operational costs over a 3-year period. Some plans may appear cheaper upfront, but they may require you to purchase additional features or be locked into a monthly subscription, which can end up being more expensive in the long run. Conversely, plans that involve transferring your own code and domain registration may seem more expensive initially, but they give you more control over your website in the long run, allowing you to choose your own hosting provider and maintain the site yourself if needed. The final cost will vary depending on the specifications and traffic, but the key is to calculate the total cost over 3 years. - One-page website, WordPress, fully customized – how to choose? There is no "best" option; the ideal choice depends on your current goals. A single-page (landing page) is suitable for promoting a single event or product, offering quick setup and low costs, but it has limited pages and SEO content capacity. WordPress is a mature, open-source system with a rich ecosystem of plugins, making content creation and editing easy. It's practical for content-focused websites or when budget is a priority. However, managing a large number of plugins requires careful attention to performance and security. Fully custom development (using Next.js) offers the greatest flexibility in terms of performance, unique workflows, and complex integrations, making it ideal for long-term operation, websites requiring unique features, or those with high traffic. The downside is that it requires a higher initial investment. It's better to carefully consider what your website will look like in three years and then choose the best option, rather than simply selecting the cheapest one upfront. - Is it possible to create a decent website with a budget of 50,000 TWD? Yes, but with more limitations: 5-8 pages of static content, using an existing design style, and without complex features. If customization is required, such as visual design, membership system, e-commerce, or backend management, a budget of TWD 150,000 or more is recommended. - What is the approximate annual maintenance cost for a website after it has been launched? The level of maintenance you require will determine the cost. If you simply want to keep the website online, the main expenses are domain registration (a few hundred dollars) and hosting (ranging from a few thousand to several million dollars depending on traffic). If you plan to regularly update content, fix bugs, and make changes, you'll likely need to pay a monthly fee or an hourly rate. It's best to clarify upfront: what is covered under the warranty, and what additional costs might apply. These figures are just estimates; the actual cost will depend on the website's specifications and traffic volume. - What exactly does "SEO optimization" on a quotation mean? A reasonable scope for the initial website development phase includes: meta tags, sitemap, robots.txt, structured data, loading speed, and mobile-friendliness. These are essential for ensuring that search engines can correctly index the website, but they are distinct from ongoing keyword content management after launch. If a quote promises ranking, it should be treated with caution. - I'm halfway through the website development and I'm considering switching vendors. Is this feasible? This depends on the contract and delivery terms. If the source code and design documents are clearly owned and the main domain is registered under your name, then the receiving party should be able to continue working on them. However, if the majority of the completed work is within the vendor's environment, it will likely require a complete redo. This is why it's crucial to discuss ownership terms before signing the contract, rather than trying to negotiate them later. - Is it possible to upgrade from a template website to a customized one later on? Yes, and it's a reasonable approach for many small businesses: start with a low-cost, basic website to validate the business and its demand, then customize it later as traffic and needs grow. However, it's important to note that "upgrading" essentially means rebuilding – the templates and features of a platform are usually not transferable. What can be transferred are the domain, content, and existing rankings (through 301 redirects). When planning, it's best to purchase the domain under your own name, which will make future transfers much smoother. ### Website SEO Not Working? Common Technical SEO Issues to Consider URL: https://www.falconinformation.com/en/blog/common-seo-mistakes SEO efforts didn't result in any ranking changes? In most cases, the problem lies in the technical aspects rather than the content. This article summarizes the most common technical SEO issues we encounter when taking over client websites. If SEO efforts aren't yielding results, it's important not to immediately assume the problem lies in the length of the content or to attribute it solely to technical issues. The correct approach is to first verify the search requirements, indexing eligibility, page quality, and measurement accuracy, and then analyze external competition. This article outlines the technical issues that Falcon typically identifies when checking a website, as well as how to avoid making widespread changes to the entire site at once. - Common SEO Technical Issues The following is not a fixed list of frequencies or ranking factors, but rather a list of potential risks that should be prioritized when redesigning or taking over a website: - The core content loads slowly or the layout shifts, making it difficult for users on mobile devices to complete tasks. - There is no mobile version or a poor mobile experience. - robots.txt: Preventing important pages from being indexed - Sitemap is incomplete or not submitted. - Canonical tag (causing Google to identify as duplicate content) - There is a mixed content issue with the HTTPS configuration. - Inconsistent data structures and screen displays, or the creation of duplicate entities, can lead to errors. - Images that lack appropriate alt text or dimensions are not accessible to users who rely on visual information. - The key content is rendered using JavaScript, and cannot be accessed by web crawlers. - The internal linking structure has become corrupted, causing important pages to become isolated and inaccessible. - First, determine the specific layer or area where the problem originates based on the available evidence. First, check Page Indexing, URL Inspection, and Performance in Search Console. Then, reproduce the issue using a real browser, Lighthouse, or a crawler. Third-party tools can only provide clues, but they cannot replace Google's actual canonical data, indexing status, and query data. If a website isn't appearing in search results, first check for indexing and topic relevance. If it's appearing but not getting clicks, then check the title, meta description, and search intent. If it's getting clicks but not leading to conversions, the problem may lie in the service content, evidence, or conversion process. Choose the first diagnostic point based on the symptoms. - Symptoms - First, check - Don't do it yet. - - The critical page was completely unexposed. - Indexing, canonical URLs, robots.txt, internal linking, and query relevance - Extend all articles in bulk - - Has high visibility but low click-through rate. - Identify the user's intent, title, and description, and then compete with the search engine results page (SERP). - Directly change the URL or delete the page. - - Clicking the button resulted in normal operation, but no order was placed. - Case studies, pricing, calls to action, and service suitability - Only focus on the average ranking. - - Overall, the revisions resulted in a decline. - Publication time, URL redirection, noindex, content differences, and performance - Also, modify all templates and content. - Debunking Common SEO Myths, Effortlessly When taking on new clients, we often need to debunk some widely circulated but ultimately inaccurate claims. For example, the idea that "a higher DA/DR score leads to better rankings" – Google has never publicly disclosed its ranking algorithms, and DA/DR are estimates provided by third-party tools like Moz and Ahrefs. They should only be used as relative references and not as guarantees of results. Another common misconception is that "a high bounce rate negatively impacts rankings." Bounce rate and dwell time are not direct ranking factors according to Google. Instead, the focus should be on improving user experience and page loading speed. Finally, the claim that "Meta keywords should be stuffed with relevant terms" is outdated. Google no longer considers this a significant ranking factor. Instead of wasting time on these misconceptions, it's better to focus on building a solid technical foundation and creating high-quality content. - My ranking has suddenly dropped, so don't immediately blame the content. When rankings fluctuate, the first step is to determine whether the cause is "external" or "internal." External factors refer to Google's core algorithm updates, which occur periodically and can significantly impact the rankings of entire industries. In this case, the focus should be on the overall quality of the content and the E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) rather than a single page. Internal issues might include accidentally adding "noindex" after a redesign, forgetting to set up 301 redirects when moving the website, slow page loading times, or being flagged for having low-quality backlinks. Our approach is to first use Search Console to analyze the timeline – to see if the drop in ranking coincides with any known algorithm updates or any changes we made ourselves. Then, we determine whether to focus on technical fixes or content improvements, rather than making sweeping changes to the entire website based on a single ranking drop. - The order of repair should prioritize minimizing secondary damage. First, save the original URLs, canonical tags, indexing information, and performance metrics before making any changes. Prioritize fixing errors that affect crawling and indexing, then address issues with the main page content and internal links, and finally, address low-impact warnings. For each deployment, record the date, affected URLs, and expected results. After deployment, verify that the crawler retrieves the correct HTML, and then monitor search trends over several weeks or months. Do not repeatedly change titles, URLs, or topics simply because there has been no increase in traffic for seven days. - Should I inspect it myself, or should I hire a contractor? Basic issues (such as sitemap, HTTPS, and mobile-friendly design) can be identified and addressed independently using GSC and Lighthouse. More complex issues (such as canonical conflicts, JavaScript rendering, and internal linking restructuring) typically require the expertise of experienced professionals. - Are claims that a company can "guarantee first-page rankings" true? Treat it as a red flag. Rankings are determined by Google's algorithm, and no company can guarantee a specific position. Those who attempt to "rush to the top" often use methods that will be penalized by the algorithm, putting your website at risk. We prefer to set conservative expectations rather than making such promises. - Once the technical issue is resolved, how long will it take for the improvement to be reflected in search performance? Updating your website with Google usually takes several weeks to several months, depending on the severity of the issue and the competitive landscape. After making the changes, use a URL checker tool to confirm that Google has indexed the new version. Then, monitor the trends – don't repeatedly change the title or URL if there's no activity for several days. - Search technical requirements https://developers.google.com/search/docs/essentials/technical Google Search Central - Performance report: Common tasks and use cases https://support.google.com/webmasters/answer/17010961 Google Search Console Help - Debugging drops in Google Search traffic https://developers.google.com/search/docs/monitor-debug/debugging-search-traffic-drops Google Search Central ### AI Customer Service Systems: Comparing the Costs of Building Your Own vs. Using SaaS URL: https://www.falconinformation.com/en/blog/ai-customer-service-cost Should AI-powered customer service be built in-house or use SaaS solutions like Intercom AI or Zendesk AI? This article compares the long-term costs, technical requirements, and suitable scenarios for both approaches. AI-powered customer service is the most common entry point for companies adopting AI in 2026. However, the long-term cost difference between "building in-house" and using "SaaS" solutions can be significant. This article provides a framework for understanding the cost structures and methods for calculating total costs over three years (actual costs will vary depending on the licensing model and usage volume). - SaaS AI Customer Service Cost Reference The biggest challenge in comparing SaaS solutions lies in the different pricing models: some charge per successful conversation, others charge a monthly seat fee, and some offer package deals. Comparing prices directly is not meaningful because you need to convert them into a monthly cost based on your conversation volume. Below are the price ranges published by each service provider (please refer to the latest pricing information from the specific brand): - Intercom Fin: Starting at just USD 0.99 per conversation - Zendesk AI Agent: Pricing varies depending on the licensing option, typically starting from USD 50 per agent per month. - Salesforce Einstein: Significant Differences in Performance Across Different Configurations - Cost structure of building an AI-powered customer service system The costs of building a system can be broken down into three distinct categories: development costs, API usage fees, and maintenance costs. Each category has different characteristics: development costs are a one-time expense, API usage fees vary depending on usage, and maintenance costs depend on whether you choose to outsource it or handle it internally. Separating these costs allows for independent decision-making for each category – for example, you could initially outsource maintenance and bring it back in-house once the team is fully trained. For example, using Falcon's publicly available pricing: - Falcon MVP Development: One-time cost of TWD 25,000-37,500 - AI API Costs: $5,000 - $30,000 per month (API costs are based on actual usage and are priced at the original rate). - Falcon maintenance costs: TWD 2500-7500 per month (options for monthly packages or hourly rates) - How to calculate the total cost over three years When comparing the two options, it's recommended to calculate the total cost for three years using the same formula: SaaS three-year cost = (monthly fee or per-solution fee × your monthly conversation volume) × 36 months + setup fees; self-built three-year cost = one-time development cost + (API monthly fee + maintenance monthly fee) × 36 months. Two reminders: First, conversation volume is the most critical variable – when the volume is small, SaaS is almost always cheaper, while a large volume will dilute the fixed costs of self-building; Second, the price of SaaS may vary depending on the plan, and the price of the API for self-building may also fluctuate. To get a more accurate result, use ranges instead of single points. We will help clients calculate this formula in detail when providing a quote, rather than simply saying "long-term, it's more cost-effective." - When should you choose SaaS? To be honest, in many situations, SaaS is a more reasonable choice, and we would recommend this approach. - Requires immediate deployment (SaaS typically within 1 week, on-premise requires 3-4 weeks) - The team does not have IT personnel to maintain the system. - The customer service process is standard and doesn't require a lot of customization. - The number of customers is still low, and the average number of conversations per month is less than 1,000. - Under what circumstances is building your own home more cost-effective? Conversely, self-built long-term costs and flexibility often prevail when the following conditions are met: - High volume of communication (low marginal costs due to self-service) - Requires connection to internal systems/databases - There are regulatory requirements (for certain industries, such as finance and healthcare) - I hope to avoid being tied to long-term licensing fees. - The costs associated with switching from a Software-as-a-Service (SaaS) model to an on-premise solution (or vice versa). Many companies actually start by using SaaS to validate and scale, and then build their own system later. This approach is viable, but the transition is not free. When planning, it's important to factor in the following four costs: 1. Knowledge Base Portability: Well-organized Q&A and documents are valuable assets. When choosing a SaaS solution, ensure you can fully export them in a usable format. 2. Conversation History: Historical conversations are valuable for training and optimization. Before switching, clarify the export limitations. 3. Process Re-mapping: Any existing workflows that rely on the SaaS system, such as notifications, human handoffs, and ticket management, need to be re-implemented. 4. Dual-System Parallel Run: Running both the old and new systems in parallel for a period of time, incurring costs for both. The reverse approach (building your own system and then switching to SaaS) is often less expensive because the data is already in your possession. This is also why we include "data ownership" as a standard deliverable. - How to measure success after implementation: Key metrics to track Many people assess the effectiveness of AI customer service solely based on whether they perceive it as "more intelligent," which makes it difficult to convince business owners to continue investing. It's recommended to agree on several measurable indicators from the outset: the percentage of conversations that are resolved without human intervention, the average first response time, customer satisfaction (CSAT), and changes in labor costs or average handling time. It's important to be honest and acknowledge that these metrics will vary significantly depending on the industry, the complexity of the issues, and the maturity of the knowledge base. Avoid simply adopting the "80% resolution rate" claimed by others as a target. Our approach is to establish a baseline "before implementation" and then compare the results afterward, allowing for clear and measurable comparisons rather than relying on subjective opinions. - Common Pitfalls When Implementing AI Customer Service The implementation often fails not because the model is inadequate, but because of these factors: First, the knowledge base is too messy: documents are disorganized, content is outdated, and the AI receives bad data, leading to inaccurate responses. Second, unrealistic expectations: assuming the AI can completely replace humans, leading to a loss of credibility when it encounters situations it cannot handle – the correct approach is to design a fallback mechanism for human intervention. Third, "set and forget": without regular review and updates to correct errors, the accuracy will only decline over time. Fourth, being overly optimistic and underestimating the time required for initial setup and ongoing maintenance. We prefer to address these issues upfront during the quoting process, rather than leaving you to discover them after implementation. - What technical personnel are needed to build an AI-powered customer service system? Falcon offers a "development + ongoing maintenance" service, meaning that clients only need one project manager with expertise in "communication strategy / knowledge base management." No internal engineers are required. - Can AI customer service completely replace human customer service? It's not advisable to expect AI to handle everything. AI is best suited for processing large volumes of repetitive, rule-based tasks, freeing up human workers to handle cases that require judgment or emotional support. The most successful approach is "human-AI collaboration," where AI handles the initial processing, and human experts are brought in when the AI encounters complex or high-risk situations. Treating AI as a complete solution can often lead to problems. - What types of chatbots exist? What are the key differences between them? There are essentially three types: rule-based (following a pre-defined process, precise but inflexible), AI-generated (using large language models for free-flowing conversation, flexible but requiring control to avoid hallucinations), and a hybrid approach (following a fixed process for rule-based tasks, while using AI for open-ended questions). In practice, the most reliable approach is often the hybrid one: using rule-based processes for tasks like order processing and appointment scheduling, while relying on AI for open-ended questions, combined with RAG and human oversight for safety and accuracy. - What level of preparation is required for a knowledge base to be launched? Don't wait for perfection, but aim for a minimum standard: Frequently asked questions (typically the top 20-30) should have clear answers, outdated information should be removed, and unanswered questions should be routed to a human agent. After being onboarded, review and add content to incorrect conversations on a weekly basis, which is much more realistic than aiming for 100% accuracy before being onboarded. - Can the official LINE account be used for AI-powered customer service? Yes, LINE is the most common channel for Taiwanese businesses to integrate AI customer service. By using the Messaging API, you can connect AI customer service to your official LINE account. However, it's important to note that the messaging fees associated with the LINE official account itself are separate from the API fees for the AI. ### How to assess the quality of SEO content? E-E-A-T, Evidence, and Verification Standards URL: https://www.falconinformation.com/en/blog/how-we-define-good-seo-content The content is the core of SEO, but "good content" is difficult to quantify. This article summarizes the criteria that Falcon actually uses when producing content for clients. The phrase "content is king" has been overused, but there is no single, universally accepted definition of what constitutes "good" content. This article outlines the criteria we use when evaluating whether a project is "producible" or "unproducible." - Types of content that will not be approved - Listing vague advantages ("We are the most professional, affordable, and fastest delivery service") - Any statistical figures without a source (any number that cannot be attributed to a source should either be deleted or replaced with "according to our observations") - Making disparaging remarks about competitors without providing evidence (e.g., claiming a platform is "slow" without presenting any actual data). - Number-led filler headlines that force material suitable for 1 paragraph into a list - Content generated solely by AI, without human editing or fact-checking. - Content types we recognize - Detailed process explanation (how we actually do it, including tools and steps) - Honest Limitation Statement (Who We Do Not Serve) - Verifiable data (including source links) - A clear and direct perspective (one that is willing to say "We do not recommend doing this") - Specific suggestions that guide readers on what to do next. - The E-E-A-T Pillars: Breaking down "Expertise" into actionable steps Google uses the E-E-A-T framework to assess the trustworthiness of content, which breaks down into four key areas: Experience: (Have you actually done this, used this?); Expertise: (Does the content demonstrate in-depth knowledge?); Authoritativeness: (Are you a recognized authority in this field?); Trustworthiness: (Is the information accurate and the source transparent?) While many people simply use these as buzzwords, we advocate for a more concrete approach: Experience: Focus on providing firsthand examples and real-world processes, rather than just theoretical knowledge.; Expertise: Ensure that experts review and annotate the content.; Authoritativeness: Build external recognition through authentic content and public relations, without relying on paid links.; Trustworthiness: Provide clear sourcing, limit speculation, and make contact information and company details readily available. These four elements are important signals for both Google's traditional ranking algorithm and its AI-powered summarization, and should be integrated from the very beginning of content creation. - Will content generated by AI be penalized by Google? It's not about "using AI" that triggers penalties – Google's official stance is that it targets "mass-produced, user-unhelpful content created solely for ranking manipulation," regardless of the tool used. In other words, using AI to generate drafts or organize content is perfectly fine, as long as there's human oversight. The key is whether the content includes firsthand experience and insights, whether it's fact-checked, and whether it's free of filler. Our approach is to use AI as an assistant, not an author – all external content undergoes human editing and fact-checking, which is why we're transparent about our review standards. The truly dangerous practice is "generating hundreds of articles with a single click and publishing them without anyone reading them," which is precisely the type of thin content that algorithms target. - Methods for assessing the quality of content before publication We don't rely on a single word count or keyword density to determine publication; instead, we thoroughly evaluate the search intent, originality, verifiability, responsibility, and next steps for each piece. Any piece with significant gaps should be revisited with the original data and interview transcripts, rather than relying on longer introductions to obscure the issues. Falcon Content Publishing Checklist - Targeting - Eligibility criteria - Without examples - - Search intent - The title, introduction, and main paragraph all address the same decision-making question. - Title: Discussing Costs, Content Only Highlights the Benefits - - First-hand value - Includes practical processes, case studies, visuals, observations, or clearly defined methods. - Simply reiterate the common definitions found in the search results. - - Evidence - The data, platform rules, and results can be traced back to their original source. - Citing statistics without a date or treating goals as achievements - - Responsibility - Clearly identify the author, update date, and any limitations or boundaries. - Anonymous team, no specific date, absolute commitment - - Action - Readers know how to conduct their own research, compare information, or access relevant services/case studies. - The final call to action is simply a generic sales pitch. - What criteria should I use to determine whether or not to update something after it has been published? First, save the metrics for page queries, impressions, clicks, and conversions. If you start receiving queries that don't align with your goals, adjust the title and content boundaries. If you're getting impressions but have a low CTR, check if the promises made in the search results are clear. If users are visiting your site but not taking the next step, add case studies, comparisons, or calls to action. Only update the date when official rules, product capabilities, pricing, or practical experience actually change; don't rewrite it monthly for the sake of freshness. - Must content exceed 2000 Chinese characters, and what keyword density percentage should it target? There's no such thing as a magic number. The ideal length of content should be determined by the user's search intent – some questions can be answered concisely, while forcing a content to be excessively long can dilute the key points. Keyword density is also an outdated concept; deliberately stuffing keywords will only make the content harder to read. We focus on whether the content effectively answers the user's question, rather than simply aiming for a specific word count or keyword density. - Will content generated by AI be penalized by Google? Google's official stance is to prioritize quality over the method of creation: regardless of whether the content is written by a human or AI, a large volume of content lacking originality will be penalized by the quality system. Our approach is that AI can assist in organizing drafts, but firsthand experience, data, and professional judgment must come from humans. All content must be manually reviewed before publication. - How often should the content be updated? There is no fixed frequency. Updates are made only when official rules, prices, product specifications, or practical experience change, and the modification date is clearly indicated. While changing the date to appear "fresh" without altering the content may seem advantageous in the short term, it ultimately damages the trust that readers and search engines have in the website. - Creating helpful, reliable, people-first content https://developers.google.com/search/docs/fundamentals/creating-helpful-content Google Search Central - Google Search spam policies https://developers.google.com/search/docs/essentials/spam-policies Google Search Central - Performance report: Common tasks and use cases https://support.google.com/webmasters/answer/17010961 Google Search Console Help ### What is "llms.txt"? Format, Implementation, and Honest Evaluation of Results URL: https://www.falconinformation.com/en/blog/llms-txt-implementation-guide "llms.txt" is a website navigation proposal for AI systems. This document explains its origin and format, as well as the implementation details using Next.js for dynamic generation on this site, along with an honest evaluation of the results, including Google's official stance. `llms.txt` is a file format proposal introduced by the community in 2024, using a concise Markdown format to allow AI systems to quickly understand the structure and key content of a website. We have implemented it on this site, but we want to be clear upfront: Google has stated that it will not use `llms.txt`, and it is not a requirement for inclusion or citation. This article will teach you how to use it, and also tell you what to expect from it. - Where do LLMs come from? What is their purpose? Jeremy Howard of Answer.AI proposed llms.txt in 2024-09 for a practical reason: navigation, ads and scripts clutter web pages and make them harder for language models with limited context to process. A clean Markdown summary can explain the site and point to its key pages. Its status matters: this is a community proposal, not an official standard of any search engine or AI platform. That distinction should guide how much effort you invest. - What does the format look like? The documentation is intentionally simple, consisting of a single Markdown file located in the root directory of the website. The structure is as follows: H1 tag: Website name; Blockquote tag: A brief summary of the website; H2 tags: A list of links, with a description for each link. Additionally, there is an optional file called "llms-full.txt" that contains the complete page content. This file is intended for systems that can process long documents. Both files are plain text and do not require any special headers. - H1: Website or Project Name (Required) - Blockquote: A concise summary of a passage of text, typically found on a website. - H2 Section: A list of links, categorized, with descriptions for each. - llms-full.txt (optional): The full version of the content - The project on this site: dynamic generation, not handwritten. We use Route Handlers in Next.js App Router to provide both `/llms.txt` and `/llms-full.txt`. These files are not static, handwritten documents, but rather dynamically generated content pulled from the same data layer (TypeScript files containing service, case, and pricing information) that the main website uses. They are then output as static files during the build process using "force-static". This design solves the biggest problem with handwritten files: content drift. If prices or services change, the `llms.txt` file will automatically update during the next build, preventing the situation where the website and `llms.txt` have different information – which would provide outdated information to the AI system, making things worse than having no `llms.txt` file at all. - An honest assessment of Google's effectiveness: Google doesn't need it. This is the part that most educational resources don't cover. Google's official documentation clearly states that AI functionality doesn't require any special technical expertise, and members of the search team have publicly stated that they don't use llms.txt. Whether other AI platforms read or have read this file, and whether this affects citations, remains unclear. We reviewed our server logs and found that some AI crawlers have accessed both files, but "being accessed" and "affecting citations" are two separate things, and the latter cannot be verified. Therefore, our conclusion is that llms.txt is a low-cost supplementary measure, not the core function of GEO – the true core remains the indexable content and original evidence. - When should and shouldn't we deploy it? How to decide. Reasons to do it: Extremely low cost (one file), no known risks, and the potential for the platform to formally adopt it in the future. Reasons not to do it: If someone is asking you for a consulting fee for this, or trying to package it as "essential for any AI platform" to sell – this goes against the platform's official stance and can be used as a benchmark to assess the credibility of vendors. Our message to clients is consistent: do it, but it should be considered after technical SEO, content evidence, and measurement. - How do I verify that it has been successfully deployed? Three things to check: 1) Use `curl` or a browser to directly access `/llms.txt` and verify that the response is 200 and the content is up-to-date; 2) Ensure that the content filtering and sitemap are consistent – pages marked as "noindex" should not appear in `/llms.txt`, as this would effectively be handing over content you don't want to be exposed to AI; and 3) Regularly review the server logs to see which crawlers are actually accessing the content. This is the only firsthand data you have to determine if anyone is actually reading the content. - What are the differences between llms.txt and sitemap.xml? `sitemap.xml` is the standard officially supported by search engines, listing all URLs that can be indexed by crawlers. `llms.txt` is a community-driven proposal, using human-readable Markdown to describe key website elements. The former has a clear official purpose, while the latter currently lacks a platform commitment to use it – the two are not mutually exclusive. - Is it absolutely necessary to have the file "llms-full.txt"? Not necessarily. `llms-full.txt` is the complete content version, suitable for websites with controlled content; however, for websites with a large number of pages, expanding the entire content can be too extensive and dilute the key information. Our approach is to use `llms.txt` for structured lists and `llms-full.txt` for complete paragraphs containing services and examples. - Could the absence of a file named "llms.txt" affect how AI cites sources? Based on publicly available information from various platforms, this is not the case. Google explicitly states that it does not require it. Other platforms also do not make it a mandatory requirement. The key factor remains whether the content can be indexed and whether it has credible value. It should be considered a bonus, not a mandatory requirement. - The /llms.txt file specification https://llmstxt.org/ llmstxt.org (Proposal from the Answer.AI community) - AI features and your website https://developers.google.com/search/docs/appearance/ai-features Google Search Central 2025-12-10 ### How to Choose Citation Sources When Using ChatGPT: Observation Methods and Limitations URL: https://www.falconinformation.com/en/blog/chatgpt-search-citation-observations By analyzing the official OpenAI documentation, we can confirm the crawling mechanisms used by OAI-SearchBot, ChatGPT-User, and GPTBot, as well as the methods and limitations of observing ChatGPT's citation behavior using a fixed set of queries. The answers provided by ChatGPT searches include source links, which has led to the common question of "How does ChatGPT cite sources?". The honest answer is that OpenAI does not publicly disclose its ranking formula, and any claims of knowing the "citation algorithm" are speculative. This article outlines the mechanisms that can be confirmed through official documentation, as well as the observation methods we use in practice, including its limitations. - Three types of reptiles that can be confirmed according to official documents: OpenAI has released three distinct user agents that can be controlled separately by the platform: OAI-SearchBot: Used to create search indexes, ensuring the website appears in ChatGPT's search results.; ChatGPT-User: Represents the user's immediate request to read a webpage within a conversation.; GPTBot: Used for collecting training data for the model. Each user agent has its own independent configuration in the robots.txt file. Blocking GPTBot does not mean the website will be excluded from ChatGPT's search results. Websites that want to be visible in search results should at least allow OAI-SearchBot. The three OpenAI user agents serve different purposes. - User agent - Applications - How to get ChatGPT to cite sources when searching - - OAI-SearchBot - Create a search index and display links. - Must be approved. - - ChatGPT-User - Users expect immediate page loading. - Recommended: Release - - GPTBot - Gathering training data for the model - Decide independently based on the content licensing policy. - How do citations arise? And what distinguishes between those that can be confirmed and those that cannot? Confirmed: ChatGPT searches across multiple sources to generate answers, and provides links to the sources alongside the answers. Unconfirmed: The order of sources, the reasoning behind choosing A over B, and the weighting of content features – these are areas where OpenAI has not publicly disclosed information. Most "ChatGPT Citation Factor Studies" are conducted by third parties who make inferences based on samples. While these studies can be referenced, it's important to note that they are based on inference and should not be presented as platform rules. Our position: Focus on verifying the fundamentals and rely on observation rather than speculation. - Our observation method: Fixed query set The method involves creating a fixed list of questions and regularly re-testing ChatGPT using these questions, recording the results. Key points include: Choose questions that reflect actual customer decision-making processes (e.g., comparing services, asking about pricing). Avoid simply testing brand names, as this only reflects existing knowledge.; Start a new conversation each time to avoid context influencing the answers.; Record the date, whether the brand was mentioned, and which websites and pages were referenced for each question.; Re-test the same set of questions monthly to track trends, rather than focusing on single results. This method is cost-effective, requiring only a simple spreadsheet and consistent execution. - First, let's discuss the limitations of this method. Fixed query sets have clear limitations, which we explicitly state in our reports: AI responses are inherently random, and asking the same question twice may yield different results from different sources. Responses are also affected by the user's account, location, and model version; what you observe may not be representative of what all users see. Furthermore, when the model or product is updated, the entire set of benchmarks may be reset. Therefore, it can only provide information on "our brand's relative trends within this set of questions," but cannot be used to infer market share or exposure. Any report that claims "recommended by ChatGPT" based on a single screenshot should be viewed with skepticism. - What can content be used for? Instead of chasing opaque algorithms, focus on building a verifiable foundation. This approach serves both traditional search and all AI platforms: ensuring that OAI-SearchBot can access pages (by checking robots.txt and WAF); ensuring that important content is present in plain text within HTML, rather than hidden within interactive elements; using a question-first writing structure, where a paragraph answers the question before elaborating; relying on verifiable evidence and named authors, as this increases the value of cited content; and ensuring that brand names and company information are consistent across the web, to avoid confusion. - How do you measure traffic after it has been cited? OpenAI's official instructions state that the referral URL for ChatGPT search will automatically include "utm_source=chatgpt.com". This allows you to create a ChatGPT group in GA4 using both the campaign source and session source, and then track landing pages, case studies, CTAs, and inquiries. However, this doesn't mean that all ChatGPT traffic can be tracked. Without clicks, there will be no website data, and traffic from app openings, privacy restrictions, redirects, or parameter removals may still be categorized as referral or direct. Reports should also check both UTM and referrer data, and use inquiry numbers rather than just session counts to determine value. - If GPTBot is blocked, will its content no longer appear in ChatGPT? No, it's not entirely. GPTBot focuses on collecting training data, while OAI-SearchBot uses the OAI-Search index. Combining GPTBot and keeping OAI-SearchBot theoretically allows ChatGPT to still find cited sources. Furthermore, historical training data and content from third-party websites are not subject to your current robots.txt controls. - Is ChatGPT's search functionality related to Bing's index? OpenAI and Microsoft have a partnership, and ChatGPT's search history relies partly on Bing's infrastructure. However, OpenAI has also created its own index (OAI-SearchBot), and the complete status is not documented officially. A practical approach: Use Bing Webmaster Tools to submit, but don't consider "doing Bing SEO" as a guaranteed path to accessing ChatGPT. - How often is it reasonable to repeat a test? Our rhythm is monthly, paired with quarterly reviews. Too frequent would be pointless – the random fluctuations in AI responses would obscure genuine changes; too infrequent would miss the impact of model updates. The key is to maintain consistent conditions for each retest (questions, phrasing, new dialogue). - Publishers and Developers FAQ https://help.openai.com/en/articles/12627856-publishers-and-developers-faq OpenAI Help Center 2026-08-29 - ChatGPT search https://help.openai.com/en/articles/9237897-chatgpt-search OpenAI Help Center ### How to measure the effectiveness of GEO (Google Earth Outreach)? Practical implementations with Google AI, Bing AI, and GA4. URL: https://www.falconinformation.com/en/blog/geo-measurement-guide Establish a GEO measurement architecture using Google Generative AI, Bing AI Performance, GA4, and a predefined query set, while also outlining the limitations of each data source. GEO measurement is no longer solely reliant on screenshots: Google will launch a Search Console Generative AI performance report in 2026, and Bing Webmaster Tools also offers AI Performance data. However, these tools still cannot answer the question of "how many times a brand is mentioned across all platforms," nor can they independently prove conversions. This article combines official visibility data, on-site behavior, sampling observations, and lead inquiries into a verifiable framework. - Official AI reports have emerged, but they do not represent a complete market share. The Google report measures the visibility of websites within Google AI features, while the Bing report measures the mentions within supported Microsoft AI experiences. Their platforms, focus, and available fields are all different, so they cannot be combined to form an "AI market share." Neither ChatGPT, Perplexity, nor other platforms provide a comprehensive cross-platform brand mention dashboard. Therefore, the report must separate "official mentions," "official references," "website traffic," "query sampling," and "business results" to avoid misleading conclusions. - The five measurement signals are used to answer different questions. There isn't a single metric that definitively proves GEO (Google Elevation) generates business. If there's visibility in Google Search results but no clicks, it could mean that users have already found the answer in the search results, or that the page simply doesn't have enough compelling reasons for users to click. If there are referrals but no inquiries, it's important to first check the case studies, calls to action, and service suitability before adding more content. The five signals measured by GEO - Signal - Questions that can be answered - Main limitations - - Google Generative AI - Which pages on Google AI gained the most visibility? - It is currently only available for a limited number of websites, and does not offer functionality for searching, clicking, CTR (click-through rate), or ranking. - - Bing AI Performance - Which URLs were cited, and what grounding queries did they correspond to? - The number of citations is not a measure of ranking, authority, or presentation position. - - GA4 - Where do users come from when they access the website, and what do they do afterward? - The data is only available if you click on the link; some traffic may be underestimated. - - Predefined query sets - Does the sampling problem involve issues related to brand, origin, and description? - The answers are influenced by the account, region, model, and randomness. - - Source of information - Does the visibility of AI translate into demonstrations, forms, or qualified opportunities? - It is necessary to exclude other activities, delays in conversion, and errors in customer descriptions. - Google Generative AI Report: Focusing on Impressions and Page Views, Not Pretending to Rank The dedicated reports display impressions for AI Overviews and AI Mode, and can be filtered by page, country, device, and date. The data presented may be preliminary, and charts and tables may vary due to differences in how property and page data are aggregated. Currently, the reports do not provide information on queries, clicks, CTR, or average ranking, so they cannot be used to determine which AI query generates the most clicks. Relevant exposure is still included in the general Web Performance reports. If an account has not yet been assigned dedicated reports, the non-branded query, landing page, click, and CTR data from the Web Performance reports can be used as a substitute. - Bing AI Performance: Citation count is not a measure of ranking. Bing Webmaster Tools' AI Performance provides a public preview of Total Citations, Average Cited Pages, grounding queries, URL-level citation activity, and time trends. This can help identify "which pages are being used as sources by the Microsoft AI experience" and "what phrases are being used when extracting information." The official documentation also clearly states that citations do not represent page authority, ranking, or position within a single answer. The report should acknowledge the gap when a page is cited but not clicked or queried, and should not be used to package citations as a measure of revenue. - GA4 and ChatGPT UTM: Simultaneously track campaign source and referrer OpenAI states that ChatGPT searches will automatically include the UTM parameter `utm_source=chatgpt.com`. Therefore, GA4 should check both the campaign source and the session source, and cannot rely solely on `chatgpt.com` as the referrer. Parameters and domains for platforms like Perplexity, Copilot, and Gemini may change, so it's necessary to regularly verify the actual source values. The report should not only look at sessions, but also analyze case views, service_cta_click, contact_click, and generate_lead based on the landing page. Even when the app is opened, privacy restrictions are in place, or parameters are removed, some traffic may still be attributed to referral or direct, so GA4 provides evidence of "on-site behavior" rather than "overall platform exposure". - Fixed inquiries and inquiries: Filling in blanks in official reports While keyword sets targeting ChatGPT, Perplexity, or unlinked brands may still be useful, they only represent a sample. The questions should focus on the actual decision-making scenarios of customers, using new conversations and consistent phrasing each month, and recording the date, platform, model, brand mention, URL, and page. The results can only be used to observe the relative trends of this set of questions, but cannot be used to infer market share. To determine whether the AI phone cluster is generating qualified inquiries, it is necessary to compare the results with the service=ai_voice, contact clicks, and customer-provided sources from the form during the same period. - Decide on the next step based on the data, not on the number of articles written. First, categorize the pages monthly based on their landing page and search intent. If a page has high visibility but low click-through rates, prioritize optimizing the title, description, and search summary. If a query matches the existing page's intent but the ranking is unstable, add supporting evidence, decision-making information, and internal links, without creating a new URL. Only create new articles when there is a clearly different purchasing or technical intent, and there are no existing pages on the site that can be reasonably expanded upon. If AI recommends a page that has been viewed but not queried, prioritize revising the case evidence, call-to-action, and form process, without adding more content. - Where can I find AI-driven traffic data in GA4? When creating custom reports, use both the "Session Source" and "Campaign Source" filters to select AI sources. Ensure that ChatGPT includes "utm_source=chatgpt.com" and "chatgpt.com referrer" parameters. For other platforms, maintain custom channel groups based on the actual domains and parameters received. Reports should be viewed in conjunction with "generate_lead," "contact_click," and landing page data. - The brand is mentioned in the AI output, but without a link. Is there a way to verify this? Virtually undetectable – without a click, there is no referrer, and analysis tools cannot obtain data. This is precisely why fixed query sets exist: to compensate for the blind spot created by relying solely on passive data rather than active observation. The report should explicitly identify "unlinked mentions" as a known measurement blind spot. - Do you need an AI-powered observability tool? First, it's important to manually verify the results for three months before relying on any tool. The fundamental function of most tools is the same (batch querying + record keeping), and the data is still based on sampling, not the entire dataset. Tools only offer value when the volume of queries is so large that manual methods become impractical. If you buy a tool early on, you might mistakenly use the tool's output as official data. - Generative AI performance report (Search) https://support.google.com/webmasters/answer/16984139 Google Search Console Help - Introducing AI Performance in Bing Webmaster Tools Public Preview https://blogs.bing.com/webmaster/February-2026/Introducing-AI-Performance-in-Bing-Webmaster-Tools-Public-Preview Microsoft Bing Webmaster Blog 2026-02-10 - Publishers and Developers FAQ https://help.openai.com/en/articles/12627856-publishers-and-developers-faq OpenAI Help Center 2026-08-29 - [GA4] Default channel group https://support.google.com/analytics/answer/9756891 Google Analytics Help ### What types of AI crawlers exist? Decisions regarding opening and blocking access based on robots.txt URL: https://www.falconinformation.com/en/blog/ai-crawler-robots-guide This document outlines the differences in the purposes and functionalities of major AI crawlers, including GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, and Google-Extended, as well as the framework for deciding whether to open or restrict access based on their content business models. It also includes the actual decisions made by this website. Should you allow AI crawlers to access your website? This question doesn't have a universal answer, as "AI crawlers" are not a single entity – they range from training and search engine optimization (SEO) tools to user-facing read-aloud applications. The methods of control and the consequences of blocking them vary significantly. This article first clarifies the different types of AI crawlers, then provides a decision-making framework, and finally, shares our own choices and reasons for doing so. - First, we need to distinguish between the three different uses, and then we can discuss whether to open or close them. The first category is for training: collecting content for model training, such as GPTBot and ClaudeBot. This essentially means preventing the bot from using content in future training datasets, but it doesn't prevent the use of content that has already been trained or content that has been republished by third parties. The second category is for search indexing: creating indexes and source links for AI search, such as OAI-SearchBot and PerplexityBot. This effectively prevents the bot from being able to search within that platform. The third category is for user agent: real-time fetching of specific URLs when users request it during a conversation, such as ChatGPT-User and Perplexity-User. According to Perplexity's official documentation, these requests are considered user behavior and are generally not subject to robots.txt control. Blocking them requires server-side measures. There are also two exceptions: Google-Extended and Applebot-Extended are not independent crawlers, but rather control codes in robots.txt, which control whether content can be used for training Gemini and Apple's models, respectively. In reality, Googlebot and Applebot are still used to fetch the content. - Main AI Web Scraping Tools Based on the official documentation provided by each platform (definitions of usage are based on the official documentation, and may be updated according to platform policies): The primary impacts of AI-powered web crawlers and blocking techniques - Name - Affiliation - Category - The primary effects of the blockade - - GPTBot - OpenAI - Training - This content should not be used for model training; it will not affect ChatGPT's search functionality. - - OAI-SearchBot - OpenAI - Search index - Remove the source links from the ChatGPT search. - - ChatGPT-User - OpenAI - User agent - The user was denied access when attempting to read the data. - - ClaudeBot - Anthropic - Training - This content should not be used for training Claude. - - PerplexityBot - Perplexity - Search index - Identifying the Sources of Perplexity - - Google-Extended - Google - Training control code - Not intended for use with Gemini; does not affect Google Search or AI Overview. - - Applebot-Extended - Apple - Training control code - Not for use in training Apple models. - - Amazonbot - Amazon - Index/Assistant - Usage of services like Alexa is restricted. - - CCBot - Common Crawl - Public datasets - Exit Common Crawl (a major source of training data for many models) - Decision-Making Framework: Analyzing the Business Model of the Content The axis of judgment is "What you gain and lose when AI processes the content." Public marketing content (service descriptions, case studies, articles): The purpose is to be discoverable, with open search and user-agent models posing minimal risk. Training models should align with the brand's perspective. Paid content and original databases: The content itself is the product. Blocking training models is a reasonable default. For search models, the value of driving traffic should outweigh the risk of content leakage. Media and publishing: Negotiation and licensing are key considerations. Blocking is often part of the negotiation strategy. Common principles: This is a reversible policy decision, not a one-time technical decision – first choose a position and review it every quarter. - Our selection criteria: Comprehensive openness, with the following reasons: This website's robots.txt file allows access to GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, PerplexityBot, Google-Extended, Applebot-Extended, and Amazonbot. The reason is straightforward: we are a B2B service website, and the sole purpose of our content is to allow potential clients to find us and determine whether we are trustworthy. AI platforms referencing our content to answer user questions provides exposure for us, rather than causing a loss. Furthermore, we use the "noindex" directive within the page hierarchy for pages that we do not want to be indexed (such as drafts and personal pages), rather than using robots.txt. The difference between these two mechanisms is explained in the next section. - Practical details and common mistakes The first common mistake: treating robots.txt as a privacy tool. robots.txt only blocks web crawlers from accessing specific files; it is not a mechanism for controlling access to sensitive content, which requires login and permission protection. Second: confusing crawling and indexing. robots.txt blocks crawling; to prevent a page from being indexed, you should use the "noindex" tag. However, pages blocked by robots.txt are not even able to read the "noindex" tag. Third: blocking the wrong target. Blocking Google-Extended does not affect search results, but blocking Googlebot directly removes the page from search results. You should always verify the robots.txt settings using Google Search Console (GSC) before and after making changes. Fourth: misconfigured Web Application Firewalls (WAFs). WAF rules may block crawlers while allowing access to specific files, requiring verification of actual access through server logs and official IP lists. - If I block GPTBot, will the content it generates no longer appear in ChatGPT? It will not be completely eliminated. GPTBot only focuses on collecting future training data. The references used by ChatGPT, which are indexed by OAI-SearchBot, as well as historical data and content from third-party websites that have been incorporated into the model, will also remain unaffected. To manage this effectively, you need to clearly identify which type of usage you want to restrict. - Will blocking Google-Extended affect Google's search ranking? According to Google's official documentation, this is not the case. Google-Extended only controls whether content is used for training models like Gemini, and does not affect Google Search's crawling, indexing, and ranking, nor does it affect AI Overview, which uses the standard Googlebot index. - How long does it take for changes to the robots.txt file to take effect? You need to wait for the crawler to re-fetch the robots.txt file, as the frequency varies depending on the search engine. Google typically does this within 24 hours. After making the changes, you can use the Google Search Console (GSC) robots.txt report to verify that Google has the updated version. For other platforms, monitor the server logs to observe the actual access changes. - How can I tell if it's a real snake or just a harmless imitation? The user agent string can be forged. OpenAI, Google, and Perplexity have published official IP ranges. A more secure approach is to perform IP address verification on the server or WAF, and only apply allow rules to requests that pass verification. - Overview of OpenAI crawlers https://platform.openai.com/docs/bots OpenAI Platform Documentation - Overview of Google crawlers and fetchers https://developers.google.com/search/docs/crawling-indexing/overview-google-crawlers Google Search Central - Does Anthropic crawl data from the web, and how can site owners block the crawler? https://support.claude.com/en/articles/8896518 Anthropic Support - Perplexity Crawlers https://docs.perplexity.ai/docs/resources/perplexity-crawlers Perplexity Documentation ### How to Choose an SEO Company? A Checklist for Contracts, Reports, and Acceptance URL: https://www.falconinformation.com/en/blog/seo-vendor-evaluation-guide From presentation skills and contract terms to reporting guidelines and acceptance criteria, we have compiled a practical checklist for evaluating SEO vendors. Written by us, who also provide SEO services, this checklist includes the standards you should use to assess our offerings. This article was written by us, a company that provides SEO services. We want to be upfront about our potential conflict of interest: we stand to benefit from this information, but we also understand the language and tactics used in this industry. Every check standard mentioned in the article can be used to evaluate any company, including ourselves – and that's why we felt compelled to write it. - First, make sure you know exactly what you want to buy. The term "SEO services" encompasses a wide range of different tasks: technical fixes (website optimization, indexing issues, often one-time), content creation (ongoing article and page management), or comprehensive consulting (covering strategy, execution, and measurement). The appropriate type of provider depends on your specific needs – a technically strong team may not be able to create content relevant to your industry, and a content farm-style operation may not be able to fix your website. First, determine which area you need, and what your budget is, then compare providers. Otherwise, you're comparing apples and oranges. You can find information on the cost structures of different types of SEO services on our publicly available SEO pricing page. - Red Flags in Presentation: What to Watch Out For Be cautious when hearing the following statements, as each has a specific reason behind it: - "Guaranteeing a #1 ranking" – Rankings are determined by algorithms, and no company can guarantee a top position. Tactics that aim for a quick boost often come with associated risks. - "Guaranteed to be cited by AI" – This is a typical example of GEO jargon being used, as no platform currently offers this type of service. - "We have a special relationship with Google" – Google does not offer any paid or preferential channels for organic ranking. - "Seeing Results in One Month" – Re-evaluating and assessing progress on a weekly or monthly basis, and promises of quick results often rely on manipulating short-term metrics. - "Ultra-low monthly fee, all-inclusive" – The common reality of very low-priced, all-inclusive services is that they rely on standardized, pre-packaged content, without any customization or specific measurements. - Key terms to watch out for in the contract Before signing, carefully review each clause to determine what you will retain upon termination: asset ownership – who will own the GSC and GA4 accounts? Who will own the content copyrights? Will external links be removed upon termination? Exit terms – notification period and fees for early termination, and a list of deliverables to be handed over. Scope definition – what tasks will be performed each month, how much content will be produced, and who will be responsible for reviewing. Outsourcing disclosure – whether content and links will be outsourced to a third party. Our position is clearly stated on our pricing page: the accounts should be registered in the client's name from the beginning, and you can request that any vendor follow this practice. - How to read financial reports without being misled First Principle: Request access to Google Search Console (GSC) for yourself. While you can enhance the presentation of reports, the raw data from GSC should remain unchanged – allowing you to verify it at any time. Second Principle: Distinguish between vanity metrics and business metrics. Metrics like total impressions and average ranking are easily inflated (due to long-tail keywords), while the key metrics to track are clicks on branded searches, on-site behavior, and lead generation. Third Principle: Be wary of screenshots. Search results are personalized and influenced by location, so screenshots can be misleading. Instead, ask your vendor to use GSC query data for reporting. If a report never mentions "what hasn't been achieved this month," that's also a signal. - How to design the acceptance and trial period? A reasonable acceptance design should distinguish between "assured" and "unassured" aspects: technical repairs can be verified – this includes the number of index issues, the repair list, and the status of the work, which all have objective standards. Rankings and traffic cannot be guaranteed – what can be verified is whether the work has been completed and whether the communication is transparent. Practical recommendations: break down the collaboration into a one-time technical inspection and repair (lasting one to three months, with clear deliverables), and then move into a monthly fee-based service. Initially, sign a long-term contract where all services are included, and the negotiation power is entirely with the other party. During the first review meeting, focus on two key things: can the other party clearly explain "why these actions are being taken," and is the communication consistent with what was stated in the contract? - Things you need to do: Both good suppliers and good customers are essential. The final section, which is often overlooked in purchasing guides, highlights that outsourcing SEO is not simply about handing over the problem and walking away. Effective content requires your input – case studies, expert judgment, and answers to frequently asked customer questions – which vendors cannot create. Additionally, dedicating even a half hour to an hour each month for interviews or review will significantly improve content quality. The decision-making process also needs to be aligned; if technical changes on your website take three months to implement, it's unfair to blame the vendor for a lack of progress. Before starting a partnership, ensure that someone internally can handle tasks such as providing materials, reviewing content, and approving technical changes. This person doesn't need to be an SEO expert, but they should understand your business. - Are there any affordable, all-inclusive monthly plans available? First, clarify the scope before discussing pricing. Comparing "specific tasks, deliverables, and responsible parties" for each monthly period reveals that low-cost options often involve standardized content, lack of technical expertise, and only providing screenshots in reports. Once the scope is clearly defined, it becomes apparent that some low-cost options are not actually cost-effective. - What documents can you request from the supplier before signing a contract? Verifiable public case studies (actual pages and content that can be searched and verified, rather than just screenshots), along with clear instructions on the actions to be taken and those that will not be taken, and written commitments regarding asset ownership. Screenshots of successful cases are the easiest to fabricate, so verifiability is crucial. - Should I learn SEO myself or outsource it? How do I choose? Small website, ample time, low industry competition: Self-learning the basics (GSC, technical audits, content principles) is often sufficient. The articles on this site are written with this in mind. For industries with high competition, limited time, or websites with accumulated technical debt: outsourcing is more practical – but regardless of which path you choose, you should maintain control of your own account. - What should you consider when switching SEO vendors? The handover checklist should at least include: GSC/GA4 access transfer, a list of content and copyright verification, a list of existing external links, and the status of ongoing projects. The biggest concern is that the account is registered under the previous vendor – which is why it's crucial to agree on asset ownership during the contract, rather than discovering it after the separation. - Do you need an SEO? https://developers.google.com/search/docs/fundamentals/do-i-need-seo Google Search Central - Google Search spam policies https://developers.google.com/search/docs/essentials/spam-policies Google Search Central ## Service Area ### Taoyuan SEO Company | Local Search, GBP Optimization, and Transparent Performance Measurement URL: https://www.falconinformation.com/en/local/taoyuan-seo Falcon primarily serves businesses in Taoyuan, Zhongli, Guishan, and Bade, providing SEO services. We conduct online meetings or arrange visits to clients' locations, but do not have physical stores for direct visits. Taoyuan is our home turf: Our team is based here, and we serve small and medium-sized businesses in Taoyuan, Zhongli, Guishan, Bade, Yangmei, and Pingzhen. This page is not a template-based city page; we have written down the actual search behaviors, common needs, and methods we have observed while working in Taoyuan, so you can use this information to determine whether we understand the local business environment. - Falcon's SEO Services in Taoyuan The project scope is consistent with our nationwide plan: technical checks, content, and measurement are all essential; most Taoyuan clients receive the option of face-to-face interviews, as well as firsthand understanding of local search behavior: - Comprehensive SEO Audit (Technical SEO + Content Audit) - Keyword Research and Implementation (Including "Taoyuan/Zhongli + Services" Local Long-Tail Keywords) - Monthly Content Planning and Production - Google Business Profile (GBP) optimization—the key to local search and map-pack visibility - Building Backlinks (White Hat Methods) - Observations of the Taoyuan Market: Two Distinct Types of Clients From our project experience in Taoyuan, Taiwan, we see two distinct SEO needs. Local service businesses—restaurants, renovation contractors, clinics and tutoring centers—attract customers searching for “Taoyuan + service” or “Zhongli + service.” Google Business Profiles and map results are decisive here, rather than blog articles. The other group is industrial B2B: manufacturers and processors around Zhongli, Pingzhen and Guanyin. Their buyers search using product specifications and English keywords, so they need well-structured, detailed product pages; GBP plays a supporting role. These two groups need very different budget allocations, so we identify which applies to you before quoting. - Our perspective: Google Business Profile is the most underrated asset for local businesses in Taoyuan Many small and medium-sized business owners in Taoyuan believe that "Since I operate a local business and rely on word-of-mouth referrals, I don't need to do SEO." However, in reality, potential customers will almost always search for your business name on Google, read reviews, and verify your address and phone number before deciding whether or not to contact you. Therefore, when we do local SEO for Taoyuan, we prioritize the completeness of your Google Business Profile (GBP), responding to reviews, and using local keywords (such as "Taoyuan SEO" and "Zhongli Web Design") to ensure they are as important as your website's ranking. For local businesses, the visibility of the map listing often leads to more direct calls and visits than appearing on the first page of organic search results. - Google Business Profile (GBP) optimization checklist To make it easier for potential customers to find you through local search and map packs, we recommend implementing the following steps: - Accurately fill out basic information: Name, phone number, business hours, website link; Non-storefront addresses for service businesses must be hidden - Choose the correct primary and secondary categories (If you choose the wrong category, your business will likely not appear in the map pack) - Regularly upload photos of your business, team, and products to make your profile look "active" - Respond seriously to all reviews – thank positive reviews and address negative reviews with sincerity. Responding to reviews is also a way to show potential customers that you care - Use the posts feature to update the latest news, events, and services - Fill in service details and service areas (Taoyuan, Zhongli, Guishan, and Bade, etc.) to match local searches - Verify that the NAP (Name, Address, Phone number) is consistent across the website, GBP (Google My Business), and all relevant directories to avoid conflicting information. - How to measure the effectiveness of local SEO? Unlike general website SEO audits, local business SEO requires a different approach. Simply looking at rankings isn't enough; you need to assess whether the efforts are translating into phone calls and in-store visits. Our monthly reports focus on three key data sets: 1. Changes in the visibility and click-through rates of "Taoyuan/Zhongli + Services" local keywords within Google Search Console (GSC). 2. Insights from the GBP (Google My Business) business profile – search frequency, route planning, and call/click data. This data reflects the actual actions taken by users who find your business through the map. 3. Your own records of inquiry sources (e.g., adding a question to the end of phone conversations: "How did you find us?"). By comparing these three data sets, we can determine whether to allocate your budget towards website content or your GBP business profile. - Fee Explanation SEO pricing is consistent regardless of location: the basic package starts at TWD 7,500 per month, while the growth package starts at TWD 15,000 per month. The actual work performed and the methods used are clearly stated on the SEO pricing page. The only difference for Taoyuan clients is the option to schedule an in-person interview, which is included at no extra charge. - Example of Local Taoyuan Clients Below are some of the clients we have served in the Taoyuan area. Complete data has not yet been obtained with client authorization, so here we only list the names and project types, without exaggerating the results: - Can I have an in-person meeting with your company in Taoyuan? Yes. The company does not have a physical store; we can arrange to visit clients' offices in Taoyuan based on the needs of the project. Daily communication will primarily be through online meetings. - Approximately how much does SEO cost in Taoyuan? Our SEO plans are area-independent: Basic plan TWD 7,500/month onwards, Growth plan 15,000/month onwards. The specific work items and contract termination terms for each monthly fee are clearly stated on the SEO pricing page. - How long does it take to see results with SEO in Taoyuan? There is no fixed timeframe. Factors such as crawling and indexing status, website history, competition, content quality, and external signals all affect the results. We will check monthly using GSC and actual inquiry trends, and we do not guarantee rankings within a few weeks or AI citations. - I'm doing B2B in Taoyuan, is SEO really effective? Decision-makers for B2B clients still primarily use Google to search for company information, especially long-tail keywords such as "Taoyuan + service type," which typically have lower competition and more direct conversions. - Will you help me create a Google My Business profile? Yes. GBP is a core component of local Taoyuan SEO. We will assist in creating or optimizing the profile, setting service items and business information, and recommending strategies for managing reviews. - Can I create a Google My Business profile without a physical store? Yes. Companies such as consultants, on-site service providers, and those primarily operating online can set up a profile as a "service area business" – without displaying the exact address, but still able to specify the service area (e.g., Taoyuan, Zhongli) and appear in local searches. The key is to have accurate data and correctly set the service area. ### Taoyuan Web Design Company | Corporate Website, E-commerce, and Custom System Development URL: https://www.falconinformation.com/en/local/taoyuan-web-design Falcon provides corporate websites, e-commerce platforms, and custom system development for businesses in the Taoyuan area. We use the modern Next.js technology stack, deliver complete source code, and can discuss requirements in person. We serve clients in Taoyuan across various industries, including restaurants, interior design, human resources, and e-commerce. Our pricing for website development is project-based, with the key difference being the ability to have a face-to-face discussion to clearly understand your needs. Based on our experience, the most common cause of project delays is not technical issues, but a mismatch between what the "owner envisions" and what is documented in the requirements – a one-hour conversation can often be more effective than ten emails. This is the true value that local vendors provide. This page outlines our actual practices, processes, and pricing for projects in Taoyuan, making it easy for you to compare. - Types of Websites We Have Developed in Taoyuan Our clients in Taoyuan come from all industries, with a common focus on practicality – they want tools that can generate leads and operate, not just award-winning portfolios. Whether it's a simple website to showcase a brand, an e-commerce platform with payment and membership systems, or a reservation system to replace manual scheduling, the complexity varies, but the starting point is always the same: to clearly define what the website needs to achieve. - E-commerce Platform (Including Payment and Membership Systems) - Brand Image Website - Human Resources Recruitment and Management Platform - CMS (Content Management System) – Client Can Modify Content - LINE Booking / Online Booking System - Our Perspective: Focus on What the Website Needs to Do Before Design Many people come to us for web design and say, "I want a beautiful website." But beauty is not the goal; the goal is to attract customers, generate sales, and save labor costs. When we work with clients in Taoyuan, we first spend time clarifying what the website needs to solve – is it to take reservations? Sell products? Or allow customers to find information themselves and reduce phone calls? Once this is clear, the design and functionality can be based on it, preventing unnecessary features that may not be used after launch. When budgets are limited, we prioritize features that will directly generate business. - Common Client Needs and Our Approach in Taoyuan Our project experience in Taoyuan, Taiwan, points to three common needs. First, appointments and scheduling: clinics, beauty businesses and classrooms need customers to choose their own slots and the backend to prevent duplicate bookings automatically. Concurrency control at the data layer is the key, rather than the interface. Second, e-commerce: food and retail brands need payments, logistics and membership tiers. We make promotion rules configurable in the backend so businesses can launch campaigns themselves without calling an engineer each time. Third, a credible brand presence and inquiries: B2B factories and service businesses need a website they can confidently put on a business card and inquiry forms that people actually complete. These projects should prioritize content structure and speed over animation. - Things to Confirm Before Signing Whether you choose us or another vendor, confirm these points before signing to avoid common disputes among Taoyuan clients: whose account buys the domain (it should be yours, so you remain free to change vendors); who provides copy and photos (late assets are the biggest cause of project delays, so agree on responsibilities); who maintains the site after launch and how fees are calculated (an unattended website can become a security and reputation problem after a year); and whether the quote specifies revision rounds and acceptance criteria (without them, “revise until satisfied” is a problem for both sides). We state these points in our quotes and suggest asking every vendor you compare. - Process from Needs Assessment to Delivery The typical project process for Taoyuan clients is as follows: 1) We start with a needs assessment meeting (which can be in person or online) to thoroughly discuss what the website needs to achieve; 2) We then provide a quote – listing the pages, features, modification options, and acceptance conditions in detail; 3) Once the design is confirmed, we start development to avoid mid-project changes; 4) After development, we verify each acceptance condition; 5) Upon delivery, we provide the source code, backend operation instructions, and deployment documents. Throughout the process, you know exactly where the project is and where the bottlenecks are – most project delays are not due to development, but due to a lack of content (text, photos), which we clearly mark in the schedule. - Fee Explanation Website Development: National Unified Pricing; Official Website: TWD 20,000; E-commerce Platform: TWD 45,000; Customized System: TWD 75,000 Complete source code delivery, with hosting and domain account under your name. The quotation will specify the number of revisions, acceptance criteria, and excluded items. Detailed information is available on the website development cost page. - Taoyuan Client Case Study Complete data has not been disclosed to clients for approval; only the names and project types are listed: - How much does web design in Taoyuan cost? Pricing is consistent with national standards: corporate websites from 20,000, e-commerce from 45,000, and customized systems from 75,000. Actual pricing depends on the complexity of the requirements. - Can we discuss the requirements in person? Yes. The company does not have physical stores that clients can visit directly. We can arrange to visit clients in Taoyuan based on the specific needs of the project. We can also use online meetings for daily discussions. - How long does it take to build a website? Corporate websites typically take 4–6 weeks, while e-commerce or systems with back-end functionality typically take 8–12 weeks. The actual time depends on the complexity of the requirements and the speed at which the necessary materials (text, images) are provided. The clearer the requirements, the better we can control the timeline. - Can I update the content myself after the website is launched? Yes. We will set up a CMS back-end and provide training, allowing you to update text, images, and news yourself on a daily basis. You don't need to come back to us every time. - How is maintenance after launch calculated? Pricing is based on the scope of maintenance, with options for monthly fees or per-service charges. The quote will list the items included and excluded. Because the source code and account are in your name, you will not be blocked from maintaining or switching to a different vendor later. - Do you offer services in the areas of Zhongli and Nei-Li? Yes. Our services cover the entire Taoyuan area, and we have a significant client base in the Zhongli area. We can arrange meetings at your company, and we can also communicate via online channels for daily interactions. - Can I start with a one-page website and expand it later? Yes, this is a reasonable starting point when the budget is limited. We will set up the basic structure, and you can expand it to multiple pages or add a back-end later without having to rebuild. The key is that the domain and hosting must be in your name from the beginning. - If you have a physical store, should the website and Google My Business listing be created together? We recommend creating them together: the website handles branding and detailed information, while the Google My Business listing handles map visibility. Having consistent names, addresses, and phone numbers is essential for verification. A complete list of GBP optimization tips can be found on our Taoyuan SEO page. ### Taipei Digital Marketing | SEO, Advertising, Social Media, AI Integration URL: https://www.falconinformation.com/en/local/taipei-digital-marketing Falcon provides integrated digital marketing services for businesses in the Taipei area: SEO, Google Ads, Meta Ads, social media management, and AI tool implementation. We primarily operate online, but we can also arrange to meet you in Taipei. Taipei is the most competitive market for digital marketing in Taiwan: advertising costs are high, content requirements are stringent, and every industry has a cluster of companies vying for the same key terms. This page explains how we serve clients in Taipei, and how we believe budgets should be allocated to avoid dilution. When comparing different agencies, you can also use this page's service and pricing information as a benchmark and ask the same questions of other agencies. - Our Service Packages Individual services can be commissioned separately or combined. The key is to start with a diagnosis, not to buy everything at once – all channels in the Taipei market are expensive, and money should be spent where your clients are actually present. Often, the result of this is "just do two things initially": - SEO Technical Foundation and GEO Content Optimization - Google Ads + Meta Advertising Management - Social Media Management (IG, FB, LINE, TikTok) - AI Tool Implementation - Website Development and Optimization - Short Video and Branding Video Production - Observations about the Taipei Market: Budget Dilution is the Biggest Risk Based on our experience working with Taipei clients, the key characteristic of this market is "everything is expensive, everything is competitive": the cost per click for popular keywords is high, and the content requirements for SEO are also stringent. Social media is also dominated by every brand. The most common mistake Taipei clients make is not allocating their budget, but rather spreading it across all channels. Doing a little bit on each channel without focusing on any one, resulting in no noticeable results. Our recommendation is always to start with a diagnosis: identify where your clients are actually coming from, and which channel offers the most cost-effective customer acquisition. Focus your budget on the top one or two channels, and maintain a basic presence on the others. - Should you commission individual services or an integrated package? The decision is simple: address your biggest bottleneck first. If your website is poor and you have no search traffic, start with SEO; if you have traffic but no conversions, focus on improving your website and conversion paths; if you need to generate leads quickly, start with advertising while also laying the foundation for SEO. The value of an integrated package lies in the data sharing between channels (e.g., advertising keywords feeding into SEO keyword selection, and SEO content informing landing pages for advertising). However, this synergy only exists if all individual services are done well. - Our Perspective: Taipei clients choosing a company in Taoyuan is not about quality, but about convenience SEO audits, content creation, and reporting are primarily conducted online. If interviews or workshops are required, we can arrange visits to clients based on project needs. The location of our team does not guarantee results, and you should still compare the scope of work, measurement methods, case studies, and the clarity of the responsible person. - When would we advise you not to sign an integrated contract? We would directly advise against this in two situations. The first is when the budget is insufficient to support multiple channels. Instead of doing a partial job on each channel, it's better to concentrate the entire budget on a single channel to achieve results. The second is when there is no internal person to coordinate. Integrated marketing requires someone to provide materials, review content, and make decisions – if this role is missing, then multiple channels will simply operate independently. In these situations, we recommend starting with individual services, and then discussing integration once the foundation and resources are in place. While this may mean missing out on a potential deal, it's better than wasting both your time and money on a project that won't deliver results. - How to measure results across different channels? A common problem in integrated marketing is that every channel claims credit for results. We first establish a shared measurement foundation: advertising and social links carry UTM parameters, and GA4 records inquiry actions such as form submissions, phone-link clicks and LINE joins as events. The monthly report compares traffic, engagement and inquiry contributions from all channels in one table. SEO and AI search are also tracked through GSC and referral data. With this foundation, decisions about which channels deserve more investment follow the data, rather than whoever gives the best presentation. - Fee Explanation Pricing is consistent regardless of location. The following are the starting prices for each service: SEO Basic: starting at TWD 7,500/month, GEO: starting at TWD 12,500/month, Website Setup: starting at TWD 20,000/project, AI Customer Service MVP: starting at TWD 30,000/project. Advertising management and social media management pricing will be quoted separately based on the scope of work (advertising costs will be paid directly from your advertising account, without any additional fees). The complete pricing details and factors are publicly available on the pricing page. - Our company is in Taipei. Would working with a Taoyuan vendor be inconvenient? Online meetings (Google Meet / Zoom) can handle most communication needs. If an in-person meeting is required, we can meet in Taipei. The frequency of meetings will be determined based on the scope of the project. - How much does digital marketing in Taipei cost? The cost depends on the service package. The following are the standard starting prices for each service: SEO starting at 7,500/month, GEO starting at 12,500/month, website starting at 20,000, and AI customer service MVP starting at 30,000. Advertising and social media management pricing varies depending on the scope of work. We will first assess your needs and then recommend a suitable package. We don't recommend a full package upfront. - Can I just hire someone for a single service? Yes. While integrated marketing offers greater synergy, we can also handle individual projects (such as just SEO or just advertising management). - Should I focus on advertising or SEO first? It depends on your urgency and needs: if you need to generate leads quickly, start with advertising, while also building a solid SEO foundation. If you don't need immediate results, focus on building your website and SEO first, as it provides the foundation for effective advertising. The key data from both SEO and advertising can be used to inform each other, which is the true value of doing both simultaneously. - How is advertising cost calculated? You pay the advertising platform directly through your own advertising account. We charge a management fee for our services – the two payments are separate, and the invoices are transparent, allowing you to see the actual advertising spend and performance data at any time. - Do you have a physical meeting space in Taipei? No, we don't have an office in Taipei. Meetings are typically held at the client's office. This is a deliberate choice: the cost savings are reflected in the pricing, and it's also why we clearly outline our service offerings on our website. - How often will I receive reports? The standard reporting frequency is monthly, with bi-weekly check-ins for advertising management. Reports include access to the original data from GA4 and all platforms, allowing you to log in and verify the data yourself, rather than just relying on our summarized reports. ### Taipei SEO Company | Technical Audits, Content Strategy, and Transparent Performance Measurement URL: https://www.falconinformation.com/en/local/taipei-seo Falcon provides SEO and GEO services for businesses in the Taipei area: technical audits, keyword research, content optimization, verifiable evidence, and search performance measurement. We primarily work online, and you can schedule a meeting to discuss your needs. Most of the SEO tasks (audit, keyword research, content creation, reporting) are completed online, and the location of the vendor is not a major factor. This page, besides explaining the service, also reflects our observations about the Taipei SEO market – the content requirements are completely different from other cities in the most competitive search market. The pricing section and FAQs are also suitable as a checklist when comparing different vendors. - Our SEO Services The solutions provided to Taipei clients are consistent with the national standard: technical foundation, content aligned with search intent, and results verified with data that you can access yourself. The specific tasks include: - Comprehensive SEO Audit (Core Web Vitals + Schema + Mobile-First) - Keyword Research and Content Strategy - Monthly In-Depth Content (as per plan) - Building Backlinks (White Hat Methods) - Local Taipei Keyword Optimization - GEO-Friendly Citation and Source Disclosure - Observations on the Taipei SEO Market: The key is content depth Our project experience suggests two characteristics of the Taipei search market in Taiwan. First, commercial keywords are already actively targeted: the first page for legal, aesthetic medicine, financial and B2B services contains institution-level content. A few short blog posts of around five hundred Chinese characters will not realistically compete; deeper content or a focus on long-tail and local keywords is needed. Second, Taipei searches are more granular. Combinations such as “MRT station + service” or “shopping district + service” are common, requiring more detailed local keyword planning than in other cities. These observations shape our advice to Taipei clients: use long-tail and local keywords to establish cash flow first, then gradually build content assets around core keywords. - Our Perspective: SEO is an online job, the vendor's location is not important The SEO audit, keyword research, content creation, and reporting are primarily done online. What's important to compare is whether the methods are verifiable, whether the reports align with your inquiries, and whether they use illegal backlinks or a large amount of low-quality content. The location itself does not constitute an advantage in terms of quality or price. - Measurement and Reporting: You can verify at any time Our reporting principle for Taipei clients is "verifiable": We provide you with access to GSC and GA4 from the first day, and you can log in and verify every number in the report. The monthly report typically includes: search and click trends for non-branded queries, changes in rankings for key pages, the distribution of inquiry sources, and the work plan for the next month. We don't use screenshots as proof (individual search results are personalized, so you can choose which ones to show), and we don't use generic figures as the main indicator. If you are comparing vendors, we recommend asking "Can you provide me with access" as the first screening question. - Three Common Types of Taipei Client Needs Based on our experience, Taipei clients can be broadly divided into three types: professional service providers (law, accounting, medical, consulting): stable search volume, high value per transaction, but with professional content requirements – the key is to convert the expertise of professionals into content, and we are responsible for the structure and SEO. B2B businesses: buyers search for solutions and specifications, focusing on the credibility of the service page and case studies, rather than mass-produced blog content. E-commerce and D2C: the logic of traffic is completely different, product page structure, category strategy, and speed optimization are the main battlefields. The content strategy and budget allocation for these three types are different, and we will identify your type during the audit phase. - Fee Explanation Unified SEO Scheme Nationwide: Basic Scheme starting at TWD 7,500/month, Growth Scheme starting at TWD 15,000/month; GEO Scheme covering AI search measurement starting at TWD 12,500/month. Each tier includes specific tasks, contract terms, and exit options. These details are publicly available on the SEO pricing page. Before signing any contract, it is recommended to request the same level of transparency from the vendor. - Taipei SEO market situation? SEO vendor pricing varies greatly, ranging from a few thousand to tens of thousands of yuan. Our pricing structure: basic 7,500/month, growth 15,000/month, nationwide standardized pricing; before signing, it's important to compare the actual scope of work, rather than just the total price. - How to arrange meetings with Taipei clients? We will arrange the frequency of visiting Taipei for meetings based on the size of the project. Most clients find that online meetings are more efficient (without the need to commute). - With the intense competition for keywords in Taipei, are there opportunities for small and medium-sized enterprises? Yes, but the approach should be: first, focus on long-tail and local keyword combinations (low competition, clear intent), build content assets and gather inquiries, and then gradually challenge core keywords. Spending a large budget on keywords from the beginning is usually the least efficient. - How long does it take to see results from SEO? There is no fixed timeframe. Index status, website history, competition, and content quality all have an impact. We check monthly using GSC and inquiry trends, and we do not guarantee rankings within a few weeks. We also advise treating such promises as a red flag from potential vendors. - Is it necessary to redesign the website to do SEO? Not necessarily. We will first assess the technical quality of the existing website. Most issues (indexing, speed, structure) can be fixed on the existing website. We will only recommend a redesign if the technical debt is too high to fix. We will clearly explain the reasons to you. - If the company already has a marketing team, can we just purchase a website audit or consulting services? Yes. Many Taipei clients prefer a model where internal teams handle execution, while external consultants provide technical expertise and direction. The scope of website audits and consulting services will be customized based on your team's division of labor, with execution handled internally. - Do Taipei-based businesses need to do GEO (AI search)? It depends on the industry. Industries with long decision-making processes and customers who do research (e.g., B2B, professional services) already have clear AI search behavior. Retail and local services typically prioritize SEO and business listings first. We will use fixed query sets to test your industry's current situation and provide recommendations. - Will there be additional fees for meetings? No. The regular meetings included in the monthly fee are based on the size of the project. Additional fees will only be charged for workshops or training sessions that exceed the normal frequency, and the amount will be clearly stated before execution. ### New Taipei SEO company | Banqiao, Xinzhuang, Zhonghe, Sanchong URL: https://www.falconinformation.com/en/local/xinbei-seo Falcon provides SEO services for New Taipei businesses, covering Banqiao, Xinzhuang, Zhonghe, Sanchong, Tamshui, Linkou, and other administrative districts. Keyword targeting is based on the administrative district. SEO for New Taipei City: Due to the large geographical area and dispersed industries of New Taipei, with service-based businesses in Banqiao, small-scale manufacturing in Xinzhuang and Sanchong, and a concentration of startups in Linkou, search behavior and keyword structures differ. This page explains our service methods in New Taipei, the actual order of dividing administrative districts for SEO, and why a comprehensive SEO strategy for New Taipei cannot treat the entire city as a single market. - New Taipei Administrative Districts We Serve Travel from Taoyuan to various districts in New Taipei typically takes less than an hour. Appointments for meetings and on-site interviews can be arranged. Communication primarily takes place through online meetings: - Banqiao District - Xinzhuang District - Zhonghe and Yonghe Districts - Sanchong and Luzhou districts - Linkou and Wugu Districts - Danshui and Balin Districts - Key Points for Local SEO in New Taipei Search volume in New Taipei is dispersed across various administrative districts. Strategically, focus your resources on the districts where you actually conduct business: - Long-tail keyword strategy using "Administrative District + Service" - Complete Google Business Profile - Optimize for mobile device experience (most local searches occur on mobile phones) - Integrate SEO technical foundations with GEO content optimization - Our Perspective: When targeting New Taipei, focus on keywords related to specific administrative districts. New Taipei City in Taiwan covers a large area with dispersed industries, and its search behavior differs from Taipei. Taipei residents often search for “MRT station + service,” such as “Zhongshan dentist,” while New Taipei residents more often use “district + service,” such as “Banqiao dentist” or “Xinzhuang web design.” We therefore plan New Taipei SEO by districts such as Banqiao, Xinzhuang, Zhonghe and Linkou, together with the relevant Google Business Profiles, instead of treating the entire city as a single market. For a local business, establishing visibility in its own district is far more practical than competing for broad citywide keywords from the outset. - Common types of customer needs in New Taipei Based on our project experience, demand in New Taipei broadly falls into three business groups. Local service businesses in Banqiao, Zhonghe and Yonghe—healthcare, beauty, restaurants and tutoring—need district keywords plus Google Business Profile (GBP), much like local businesses in Taoyuan. Small manufacturers and wholesalers in Xinzhuang, Sanchong and Wugu need product specification keywords, structured product pages and a B2B inquiry path. Startups and newly relocated businesses in Linkou often have little branded search demand, so they first need content and long-tail keywords to build visibility. These groups require very different budget allocations, so our audit starts by identifying yours. - The order in which to optimize for district-specific keywords In practice, we approach New Taipei keywords in three layers. First are core combinations for your district, such as “Banqiao web design”: moderate search volume and clear intent make these the priority for service pages and GBP. Next comes expansion into neighboring districts—for example, from an established Banqiao presence into Zhonghe and Tucheng. Dedicated content sections should address these areas instead of stuffing every district name into one page; readers dislike that approach, and search engines can recognize it. Citywide “New Taipei + service” keywords come third: they face the strongest competition and broadest intent, so we tackle them after building content assets in the first two layers. Reversing that order spends the budget on the hardest terms and may yield almost no return during the first few months. - Managing GBP for businesses in multiple districts A common situation in New Taipei is that businesses operate across multiple districts – for example, a Banqiao store, a Xinzhuang office, and a Zhonghe warehouse. The principle for Google My Business listings is to only list businesses with physical locations and staffed personnel. Each location should have its own listing, and each listing should have its own reviews and posts. Listings for pure warehouses or locations without personnel should not be created, as this violates the platform's guidelines and is also unethical. NAP (name, address, phone number) should be consistent across the website for all locations, so that each listing has a credible landing page. Doing this will aggregate the map visibility for each district. If you do it incorrectly (e.g., using false addresses to create listings), the entire listing may be suspended. - Fee Explanation Unified SEO Plan Nationwide: Basic Plan starting at TWD 7,500/month, Growth Plan starting at TWD 15,000/month. Details of projects and exit strategies are available on the SEO pricing page. New Taipei clients can schedule consultations at no additional cost. - Can the company hold a meeting in New Taipei? Yes. We are based in Taoyuan; Banqiao, Xinzhuang and Linkou are usually within a 30–40 minute drive. We can arrange in-person meetings in New Taipei, with routine communication primarily through online meetings. - Are there differences between SEO in New Taipei and SEO in Taipei? Search habits differ slightly. Users in New Taipei prefer searches like "administrative district + service" (e.g., "Banqiao dentist"), while users in Taipei prefer searches like "MRT station + service" (e.g., "Zhongshan dentist"). Keyword strategies will be adjusted based on these local search behaviors. - How much does SEO cost in New Taipei? The pricing is consistent with the nationwide standard: Basic plan TWD 7,500/month, Growth plan TWD 15,000/month. The scope of work and factors that affect the price are publicly available on the SEO pricing page. You can check them before signing the contract. - I only have a business in Banqiao, do I need to do SEO for New Taipei? No. That is the point of planning keywords by district: fully cover “Banqiao + service” keywords and GBP first, concentrating the budget on direct conversions. Once your own district has a solid presence and you have spare capacity, evaluate whether to expand into neighboring districts. - Is a Google My Business listing important for local businesses in New Taipei? Yes, and it's often more direct than ranking in search results. Local searches often happen on mobile devices, and GBP listings are displayed in the most prominent location – the category, reviews, and service area settings on GBP directly determine whether you will appear. - Do factories that export also need SEO in New Taipei? Export buyers won't search for "New Taipei," so you should focus on optimizing for product specification keywords and English-language SEO. The value of local keywords is primarily for attracting and collaborating with local suppliers. During the audit, we will first separate these two aspects to ensure that the budget is allocated to the right areas. - Are you already running ads? Do you still need SEO? When you stop running ads, traffic stops. SEO is a long-term asset that complements, rather than competes with, advertising. The real benefit is that you can directly feed the search keywords from your advertising campaigns into your SEO keyword selection, using keywords that have been proven to work with real results. - Can I do GEO (AI search) for a business in New Taipei? Yes, the GEO solution is area-agnostic (12,500/monthly). However, for local businesses, it's generally recommended to first complete your SEO and business profile. Currently, measuring the volume of AI searches for B2B and professional services is more apparent. ### Hsinchu Web Design Company | Collaboration on Tech Industry Websites, Bilingual Websites, and NDAs URL: https://www.falconinformation.com/en/local/hsinchu-web-design Falcon provides customized website development for companies in the Hsinchu Science Park, startups, and research centers. We offer Next.js modern technology, English-language website integration, and the ability to sign NDAs. Most companies in Hsinchu are in the tech industry, and their website needs are different from those of general businesses. They often need English versions, recruitment pages, technical document downloads, and investor sections. This page explains our working methods when taking on projects in Hsinchu, as well as what we learned from collaborating with engineers with technical backgrounds, including common requirements, collaboration rhythms, multi-language architecture, and costs. These are all important considerations that have been accumulated through actual projects, which you can refer to when making internal proposals. - Common Website Needs for Hsinchu Businesses The audience for tech industry websites is not just customers, but also job seekers and investors. This means that the requirements are different from those of general businesses: - Bilingual or multilingual (Chinese, English, Japanese) - Recruitment page + ATS integration - Technical documents / white paper downloads - Investor section (annual reports, financial statements, press releases) - Product technical specifications page (complex tables, technical diagrams) - English-language SEO - Working with Technology Industry Clients Clients from the Hsinchu Science Park typically have engineering backgrounds and communicate differently than typical businesses: they need clear specifications and the ability to track progress through an order management system, rather than weekly phone calls. We align our collaboration methods with the daily tools and processes of the engineering team: - Using Next.js + React + TypeScript (familiar to most engineers) - Integration with GitHub / Slack / Linear is possible - Terms regarding NDAs, IP ownership, and source code hosting can be negotiated - Our perspective: Websites for the technology industry are not about flashy animations When building websites for technology clients, we've learned that they don't need flashy animations, but rather clear and professional explanations. Things like the ease of downloading technical documents, the completeness of the English version, whether the recruitment page integrates with an ATS, and the availability of financial reports in the investor section – these "unsexy" aspects are actually what technology websites are used for. Therefore, when we take on these projects, we first clarify who the website is primarily for (the client, job seekers, or investors), structure the information accordingly, and then discuss the visuals. We use Next.js + React + TypeScript, which are familiar to most engineers, making communication more efficient. - Collaboration rhythm for Hsinchu Science Park projects When working with companies from the Hsinchu Science Park, there are certain aspects of the process that are less common in typical projects. We have become accustomed to these: before signing, there is often back-and-forth with legal regarding NDAs and IP terms, which can be done concurrently with the requirements discussion; the contacts are typically from engineering or marketing backgrounds, and requirements can be communicated directly through work orders and wireframes, which is more efficient than presentations; before launching, there are often internal security and procurement processes to go through, which we prepare technical architecture documentation and data processing documents in advance. In terms of schedule, these processes typically take two to four weeks longer than the actual development – this needs to be factored into the schedule, rather than trying to cram everything into the development phase. For projects with internal deadlines (such as conferences, fundraising, or recruitment seasons), it is recommended to schedule backwards from the deadline, first securing the legal and security aspects. - How should a multilingual website be structured? The most common mistake with English versions for the technology industry is "doing the Chinese version, outsourcing the translation, and then just adding /en." The correct multilingual architecture should be decided in the early stages of development: URL structure (sub-path /en is a practical choice in most cases), hreflang tags to tell search engines about the language versions, separate metadata and sitemaps for each language, and the translation process – technical and marketing content needs to be reviewed by someone who understands the product; translations from pure translation agencies often reveal errors in terminology. Our recommendation is always to first launch the main language version, and then launch the second language version after the translation and review are complete. A half-finished English version will negatively impact the international image, not enhance it. - Fee Explanation Pricing is consistent nationwide: standard website, TWD 20,000; customized system, TWD 75,000. Common add-on options in the tech industry, such as multi-language support, recruitment system integration, an investor-specific area, and a technical document library, will be listed with their individual costs and ranges on the quotation. No additional charges will be added later. Complete source code will be delivered, and terms regarding IP ownership and hosting can be negotiated according to your legal requirements. - How much does web design in Hsinchu cost? Image website 20,000 project start, customized system 75,000 start, and priced consistently nationwide. Multilingual, recruitment integration, and investor section are add-on options, and their costs are listed separately on the quotation. - Can we sign an NDA? Yes, NDAs, IP ownership, and source code hosting terms can be negotiated. - Can we do SEO for the English version of the website? Yes, a multilingual website will handle hreflang, metadata, and content structure for each language version. However, it's important to note that SEO for the English version faces international competition, and keyword strategies should be planned separately from the Chinese version. - Can we collaborate with your engineering team? Yes, this is common in projects in Hsinchu. We can integrate with your GitHub, follow your code review process, and deploy to your specified environment. After handover, your internal team can maintain it. - Will a multilingual website take longer to develop? Yes, the main delay is due to translation and review. While the structure and functionality are shared, the content for each language version needs to be independently completed. We recommend launching the primary language version first, then translating and launching the second version, without waiting for each other. - Who will maintain the investor section after delivery? We will create a module that can be updated independently in the back-end: annual reports, financial statements, and press releases can be uploaded from your existing platform, without needing to contact us. If you require ongoing maintenance, we can also provide a maintenance contract based on the scope of work. - With a limited budget, can the website be developed in stages? Yes, a common approach is to launch the core pages (homepage, products, team, contact) first, and then add pages for fundraising or expansion, such as the recruitment page and the English version. The architecture will be designed with future expansion in mind, so adding pages later won't require a complete rebuild. - Do you also handle projects for academic and research institutions? Yes, the website for the ICTE International Academic Conference, which is a case study, is an academic and research project, including a paper submission system. We can coordinate with your procurement and accounting processes, but you need to factor in the time required for administrative procedures. ## Starting Price - Website and System Development: From TWD 20,000 / Project — Starting price for corporate website; pricing for e-commerce and custom systems depends on functionality, data, and integration complexity. - AI tool development: From TWD 30,000 / Project — MVP Pricing for AI Customer Service; Model fees, data preparation, and integration with company systems will be estimated based on actual needs. - SEO Search Growth: From TWD 7,500 / Monthly — Starting prices for basic technology and content optimization; pricing will be affected by content volume, website size, and industry competition. - SEO/GEO Search Growth: From TWD 12,500 / Monthly — Focus on SEO fundamentals, authentic professional content, case evidence, and AI search volume measurement, without guaranteeing citations. ## Contact Email: contact@falconinformation.com Tel: +886958801559 https://www.falconinformation.com/en#contact This document is a summary of website content and is not a guarantee of ranking or AI citation; complete evidence and limitations can be found on the corresponding HTML pages.