Contents
In short. Start with important buyer questions and the pages that answer them. Check access, evidence and practical value. Then measure indexing, impressions, citations and inquiries separately. Google AI Overviews and AI Mode use the ordinary search requirements; a special file or markup does not guarantee inclusion in an answer.
Which buyer questions actually move a sale forward
Collect questions from customer conversations, correspondence and search data. A useful list covers selection criteria, limitations, alternative approaches and the cost of a mistake. “What is marketing?” is broad for a company helping clinics increase appointments. “How do we connect advertising inquiries to attended appointments?” is closer to its buyer’s actual decision.
Assign one main page and an intended reading outcome to each question. For example, the reader should be able to compare two measurement approaches and identify the required data. If several pages provide the same answer, clarify their roles before creating more. Near-duplicate articles make both editorial work and reader navigation harder.
- List 20 to 40 questions from real customer conversations over recent months.
- Keep the ones whose answer shapes the choice of a supplier or solution.
- Assign each question one main page.
- Write down what the reader should be able to do after reading.
The answer must be verifiable, and it must be yours
Rewriting other people's articles gives AI one more identical source
Open with a short conclusion, then explain the conditions under which it applies. For a calculation, provide the formula, input definitions and a worked example. For a product comparison, state the criteria and check date. Distinguish editorial judgment from a platform requirement or a finding supported by research.
Google’s content guidance asks about originality, completeness, clear sourcing and relevant experience. Those questions provide a useful editorial filter: readers should leave better able to make a specific decision. Credit authors and experience only when they are real; an invented expert does not establish evidence.
Google's guide to generative AI search contrasts commodity content built on common knowledge with material that offers a distinct point of view and first-hand experience. Rewriting other people's articles gives AI one more identical source. Your analysis of a real case, or a calculation on your own data, offers something others cannot.
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| Question | What to provide | What the reader gains |
|---|---|---|
| Which approach should I choose? | Criteria, differences and limitations | A shortlist suited to the situation |
| How do I calculate the cost? | A formula, inputs and a worked example | A calculation with explicit assumptions |
| Why did performance change? | An investigation sequence and required evidence | A focused task for the team |
| Can I rely on the conclusion? | Sources, dates, methods and limitations | A way to judge whether it applies |
What Google says you can skip from the agency's list
Google is direct: there are no additional requirements or special optimisations for AI Overviews and AI Mode. A page must be indexed and eligible to appear in Search with a snippet. From Google's perspective, optimising for generative AI search is still SEO.
These statements cover Google Search only. Other systems run their own crawlers and rules, so a file that does nothing for Google may be used elsewhere. Google itself says it is fine to maintain llms.txt for other services: Google Search ignores it, and it neither helps nor harms visibility there.
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| What is promised | What Google says |
|---|---|
| An llms.txt file and special AI markup | Not needed to appear in Google Search or its AI features |
| Special schema.org markup for AI | There is none; structured data still helps with rich results |
| Breaking copy into small chunks | Not required: systems understand several topics on one page |
| Rewriting copy for AI | No special writing style needed: AI understands synonyms and meaning |
| Securing forum mentions | Inauthentic mentions are less helpful than they seem; spam is blocked |
| Reports on “internal Google metrics” | No third-party tool has access to Google's internal ranking systems |
Ask the developer to prove the pages are accessible
Search Console can report the status of a specific URL and test the current page. Save the check date, result and issues found. Keep three facts separate: the page can be opened, the search engine has indexed it, and it has received impressions. Establishing one does not establish the others.
Google specifically reminds site owners to confirm that crawling is allowed in robots.txt and by any CDN or hosting infrastructure. ChatGPT has its own crawler: OpenAI says sites that opt out of OAI-SearchBot are not shown in ChatGPT search answers. GPTBot, which collects training data, is controlled independently.
Give the developer a list of important addresses and ask for plain descriptions of any blockers. For example: “the main text failed to load during the check” or “a setting prevents indexing.” The deliverable should include a corrected cause and a repeat check, rather than an unexplained score from a third-party tool.
- Check each important address with URL Inspection and save the date and result.
- Open robots.txt and CDN rules: make sure Googlebot, Bingbot and OAI-SearchBot are not blocked.
- Confirm the main content is available as text, not only in an image or script.
- Fix the cause and repeat the check on the same address.
An illustrative audit: where pages drop out
Each transition needs its own work
Illustrative example: a company has 40 pages answering important buyer questions. 36 load without errors, 31 are indexed, 22 received search impressions during the quarter and 6 appeared in AI answers according to official Search Console and Bing reports. These are invented numbers to explain the method.
Each transition needs its own work. The four inaccessible pages and five unindexed ones belong to the developer. Nine indexed pages with no impressions suggest the answer does not compete with others, which is an editorial task. A promise to “get into AI” without this breakdown does not tell you where the problem lies.
| Item | Value |
|---|---|
| Important pages | 40 pages |
| Load without errors | 36 pages |
| Indexed | 31 pages |
| Received search impressions | 22 pages |
| Appeared in AI answers | 6 pages |
Illustrative example, not company data
How to measure visibility: three official reports
Google, Bing and Yandex now report on generative answers, but they count different things. Google's generative AI report in Search Console shows impressions of your URLs in AI features in Search and Discover; since 31 August 2026 it has been available to all websites. Bing Webmaster Tools counts citations in Copilot and Bing summaries under AI Performance. Yandex Webmaster shows a site's share of mentions among Alice AI answer sources.
So do not add these figures into one “reach” number. When checking AI answers by hand, record the question set, language, country, date, system and response, and track a brand mention separately from a link to a page. Our guide to measuring company visibility in AI answers sets out the full protocol.
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| Report | What it counts | Limitation |
|---|---|---|
| Google Search Console, generative AI | URL impressions in AI features in Search and Discover, devices, dates | Impressions, not clicks or inquiries |
| Bing Webmaster Tools, AI Performance | Citations, cited pages, grounding query phrases | Query phrases are a sample; public preview |
| Yandex Webmaster, Alice AI visibility | Share of mentions among sources, example queries | Last 3 months, updated weekly |
Two languages need two checks of meaning
Russian and English versions should help readers in their own context. Check product names, example currencies, channel availability and the route to making an inquiry. A translated domestic example may not explain the problem for an international reader choosing a supplier for a new market.
Build question lists separately for each language. A language switch should lead to the corresponding article. An unfinished translation can remain in the editorial plan until it provides a complete answer.
What to assign first and how to accept the work
Choose a complete topic area around one important buyer task. Assign someone to verify facts, identify the sources that may change and set a review date. Finish the answers and practical tools before expanding into adjacent topics.
At the next level, measure visits, use of useful pages and tools, and qualified inquiries. More mentions can be an informative signal, but the commercial result needs a separate assessment.
This journal is published with the involvement of WEBNOSTRA, a company that provides SEO and AI visibility services. The acceptance criteria below work with any agency or an in-house team.
- Show the buyer question and the page that answers it.
- Show the conclusion, evidence and sources with a check date.
- Show the access and indexing check for that address.
- Show first observations after publication in the official reports.
- Show visits and inquiries from the page separately from mentions.
Key decisions
- collect the questions that influence a buying decision
- provide verifiable answers and a useful original contribution
- measure visibility and commercial outcomes separately
What to discuss with your team
- Each page answers a specific buyer question
- Claims and examples are verifiable
- Access and indexing are checked by URL
- Robots.txt and CDN rules do not block the crawlers you need
- Each language version fits its reader’s context
- Mentions, citations and inquiries are tracked separately
Terms in plain language
- Indexing
- A search engine adds a page to its database; this does not guarantee visibility for a selected query
- AI citation
- A link identifying a page as a source, distinct from a brand mention
- SEO
- Work to make a website accessible and useful for search and its visitors
- GEO
- A label for work on visibility in generative answers; Google treats it as part of SEO
- robots.txt
- A file on the site stating which crawlers may access which sections
- llms.txt
- A file describing a site for language models; Google Search does not use it
Sources
- Google Search Central: AI features and your websitedevelopers.google.com · checked 31/10/2026
- Google Search Central: Optimizing for generative AI searchdevelopers.google.com · checked 31/10/2026
- Google Search Central: creating helpful, reliable contentdevelopers.google.com · checked 31/10/2026
- Search Console: URL Inspection toolsupport.google.com · checked 29/10/2026
- Google Search Central Blog: Search Generative AI performance reports in Search Console, June 2026developers.google.com · checked 31/10/2026
- Bing Webmaster Blog: Introducing AI Performance in Bing Webmaster Tools, February 2026blogs.bing.com · checked 31/10/2026
- Yandex Webmaster: site visibility in Alice AI (Russian)yandex.ru · checked 31/10/2026
- OpenAI: Overview of OpenAI crawlersdevelopers.openai.com · checked 31/10/2026