How do I define buyer questions and entities?
Start by listing the questions, products, services, people and category terms that an external knowledge base could connect to your company. A company name alone is not enough because ChatGPT, Perplexity, Gemini, Claude, Grok, Google AI Overviews and Google AI Mode may answer a category question without mentioning the company at all.
Group questions by the decision the buyer is making. Include comparison, suitability, pricing, implementation, alternatives and troubleshooting questions. Separate company-level questions from product-line questions so a strong answer about one offer does not hide a weak answer about another.
Check each question before moving on:
- Does the question represent a real buyer decision rather than a broad keyword?
- Does it identify the relevant company, product, category or use case?
- Would a useful answer need facts from more than one external source?
- Can the team tell whether the answer named, cited or omitted the company?
If a question is too vague, add the buyer context rather than guessing the answer. For example, replace "best analytics tool" with "which analytics tool suits a 40-person ecommerce team with limited technical support?" Keep the original wording and the revised wording because engines may respond differently to each.
2. Establish a baseline across all seven engines
Run the same buyer-question set across ChatGPT, Perplexity, Gemini, Claude, Grok, Google AI Overviews and Google AI Mode before changing any source or page. The baseline should record not only whether the company appears, but also which answer position it occupies, which page or knowledge source is cited, and which competitors appear instead.
A manual spreadsheet can work for a small question set, provided every prompt, date, engine, answer, citation and observed competitor is captured consistently. Cituna takes the measurement approach further by asking all seven engines the questions buyers ask every day, recording names, citations, positions, competitors and substitute pages on every plan.
Check the baseline for comparability:
- Use the same prompt wording and location assumptions where the engine allows them.
- Record the full answer, not only the first sentence.
- Mark a brand mention separately from a citation.
- Mark an answer as unavailable when the engine does not produce a result, rather than treating it as an omission.
- Keep a copy of the cited page or source title so later changes can be traced.
A baseline is useful only if it can be repeated. Avoid changing the question set after seeing an inconvenient result. Add new questions in a separate cohort and label them clearly.
3. Trace each answer to its external source
Trace every cited or implied fact back to the external knowledge source that could have influenced the answer. The first source you find is not necessarily the decisive source, so compare cited pages, linked documents, structured data, public profiles, community discussions and other accessible references for the same claim.
The important distinction is between a missing company fact and a conflicting company fact. A missing fact gives the engine little to retrieve. A conflicting fact gives it a reason to choose another source or hedge the answer. Record the exact wording, owner, last update and relationship to the buyer question for each source.
Check the source trail for:
- An outdated product name, capability or category description.
- Different company descriptions across profiles and documents.
- A competitor page that answers the question more directly.
- A page that is accessible to people but difficult for crawlers or agents to interpret.
- A citation that supports only part of the answer.
When several offers share a category, AI Visibility Across Product Lines: What to Measure helps separate company-wide visibility from product-level visibility. Use that distinction before deciding that one successful product page represents the whole business.
4. Score gaps by buyer impact and source control
Prioritize gaps by the value of the buyer question and the amount of control your team has over the missing source. The most urgent gap is not always the lowest visibility score. A high-value comparison question with a competitor citation may deserve action before a low-value informational question with no citation.
Use a simple priority record with four fields: buyer importance, current answer quality, competitor displacement and source control. Source control means whether your team can directly correct the relevant page, publish a clearer document, request an update from a profile owner or only provide supporting evidence elsewhere.
Check the ranking before assigning work:
- Does the question occur during a real selection or renewal decision?
- Does the answer omit the company or describe it inaccurately?
- Is a competitor being named because its source is clearer, not merely because it is more famous?
- Can your team change the relevant source without waiting for another organisation?
- Would correcting the source help several related questions?
If the team cannot control the source, do not treat the gap as unfixable. Create a controlled source that states the fact clearly, then identify the external pages that should reference or reflect it. If the team can control the source, fix that source before producing more general awareness content.
5. Choose the intervention for the failure mode
Choose the fix based on why the answer failed, not on the engine that exposed it. A missing definition needs a clear page section or structured explanation. A missing citation needs a durable, crawlable source with explicit claims. A wrong answer needs one authoritative correction and consistent wording across related sources.
The main intervention paths are:
- Correct the source of truth when product facts, names or eligibility details are wrong.
- Add an FAQ, schema or concise comparison section when the answer lacks a directly stated response.
- Improve page structure when important facts are buried in navigation, images or long prose.
- Publish a supporting article when the question is legitimate but no page addresses it.
- Request an external correction when a profile or directory controls the inaccurate record.
Cituna generates proposed schema, FAQ markup, llms.txt and page changes for each measured gap. Its AutoSEO can turn gaps and Search Console demand into articles, hold them for approval or publish them to a WordPress site, Shopify, GitHub repository or another CMS by webhook. Those options suit teams that want the measurement and the corrective work in one workflow, while a manual process suits teams with clear owners and a smaller question set.
Do not add llms.txt, FAQ markup or schema as a substitute for accurate visible content. Markup can clarify a supported claim, but it cannot make an unsupported claim trustworthy.
6. Repair the controlled source before requesting recrawls
Repair the page or document your team controls before asking external platforms to notice a change. State the answer in plain language, use the same product and category terms as the buyer question, connect claims to evidence and remove contradictory wording from nearby pages.
A practical sequence is:
-
Rewrite the relevant answer so the subject, audience, capability and limitation are explicit.
-
Add supporting details where a buyer would need them, such as use cases, exclusions, implementation conditions or comparison criteria.
-
Add suitable structured data and FAQ markup only when the visible page supports it.
-
Check internal links, canonical signals, robots rules, sitemap inclusion and server responses.
-
Record the change, affected questions and expected answer improvement.
Check the result as a reader and as a crawler. The page should answer the buyer question without requiring a visitor to infer the company, product or limitation. If the page is clear but the external answer remains wrong, inspect the competing source trail before making another copy change. For sites split across brands, regions or technical properties, Manage AI Visibility Across Subdomains covers the separate visibility risks that a single domain-level check can miss.
7. Test the change with a controlled recheck
Recheck the same prompts after the source has been repaired, while keeping the original baseline intact. Compare mention rate, citation presence, answer position, factual accuracy, competitor appearances and the specific source named by each engine. A better answer is not necessarily a better outcome if it still cites an outdated page or introduces a new factual error.
Use a controlled review:
- Run the original prompt set without rewriting it.
- Add a small set of related questions to test whether the fix transfers.
- Compare the cited source and wording, not just whether the brand name appears.
- Record results separately for ChatGPT, Perplexity, Gemini, Claude, Grok, Google AI Overviews and Google AI Mode.
- Check Google Search Console for changes in clicks to the repaired page when search demand is relevant.
Cituna connects Google Search Console with its visibility data so teams can compare changes in answer visibility with search clicks. A manual team can make the same comparison by exporting the relevant queries and page data, then matching them to the change record.
If only one engine changes, inspect that engine's source path rather than declaring success. If no engine changes, confirm that the page is accessible, the claim is unambiguous and the external source has had a reasonable opportunity to update.
8. Assign ownership for ongoing external visibility
Treat external knowledge-base visibility as an operating process with an owner, review cadence and escalation rule. Buyer questions change when products launch, competitors reposition and public sources drift, so a one-time audit cannot protect every answer indefinitely.
Assign ownership for four jobs: maintaining the question set, reviewing source conflicts, approving fixes and checking post-change results. Set a trigger for an unscheduled review when a competitor replaces the company in a high-value answer, a product claim changes, or an external source becomes inaccurate.
Check that the operating process includes:
- A dated prompt and answer history.
- A source owner for every high-priority claim.
- A record of changes made and pages affected.
- A decision about approval versus automatic publishing.
- A way to distinguish a visibility problem from a product or positioning problem.
Cituna can run scans, track the prompts, move fixes through the workflow and queue articles through its hosted MCP server. Its read tools are available on every plan, while Pro allows an agent to run scans, edit tracked prompts, move fixes along and queue articles. Teams choosing another approach should still require an audit trail so an apparent visibility gain can be explained and repeated.
Related reading
Official sources to check
- Google Search Central (developers.google.com)
- OpenAI Platform Documentation (platform.openai.com)
- Perplexity API Documentation (docs.perplexity.ai)
- Anthropic (anthropic.com)
Drafted with AI assistance from our own research and Search Console data, and reviewed by Rahul A before publishing. Rules and prices change; check the linked official source before you act.