Definition
An AI search visibility audit reviews whether your site can be discovered and whether key pages are clear enough to support answers and citations. It is a diagnostic of access plus answerability—not a forecast of positions inside any specific assistant or overview.
Short answer
Check robots and crawl access, inventory important entities, test whether buyer questions have direct on-page answers with evidence, and note gaps by URL. Sample what answer products show today only as a snapshot. Snapshots change; durable fixes live on your pages.
Audit steps
- Access — Confirm important paths are allowed for general crawlers and, if policy allows, discovery bots such as OAI-SearchBot. Access is necessary, not sufficient.
- Entity map — List company and product entities that should appear in answers about your category.
- Question coverage — For each priority product, mark questions as answered, partial, or missing.
- Evidence pass — Flag claims without nearby support.
- Locale parity — Compare facts across languages you publish.
- Snapshot (optional) — Record what a few answer surfaces show for branded and category questions on a given date, labeled as illustrative.
Turn findings into a blueprint: crawl fixes, content edits, new answer pages, or evidence additions. Do not convert a single chat transcript into a KPI that pretends to be stable ranking.
Document the date of every snapshot and the exact question wording you tested. Answer surfaces change. A finding from last month is a hint for prioritization, not a permanent score. The durable artifact of the audit is the list of page edits, not a screenshot from one assistant session.
Sample findings
Finding A: Product pages block important PDFs behind scripts—specs exist but are hard to cite. Finding B: Competitors appear for “food-grade gasket compatibility” because your page never states elastomer options in text. Finding C: English and Chinese disagree on plant location—entity conflict. Each finding maps to a concrete edit, not to a promised citation count.
A useful report ends with owners and sequencing: unblock PDFs this sprint, rewrite the gasket answer next, then reconcile locale facts before launching a new campaign site.
Four separate tracks
Reuse SEO Health for technical access and index issues. Use SEO Growth for intent and gap analysis. Use GEO Health for entity, answer, evidence, and consistency quality. Use GEO Growth for uncovered answer opportunities.
An AI visibility audit that merges everything into one score will hide whether you should unblock a PDF, rewrite a definition, or publish a missing comparison page. Mika keeps the tracks separate on purpose.
FAQ
How do we audit whether our site can show up in AI answers?
Verify crawlers can reach key HTML, then review whether entities, direct answers, and evidence exist for the questions you care about. Treat live answer samples as temporary snapshots, not contracts.
What should an AI visibility report contain?
Access findings, entity conflicts, question coverage by URL, unsupported claims, locale mismatches, and a prioritized blueprint. Avoid a single overall score that mixes SEO and GEO.
Why is a competitor cited when we rank in classic search?
Classic rankings and answer surfaces optimize for different presentation needs. A thinner but clearer page can be easier to quote even when your broader site still ranks for related queries.
Next step
Run a structured SEO + GEO audit to see health findings, growth gaps, and a blueprint you can act on.
Clearer entities, answers, evidence, and context make pages easier to understand and reference. Results in any answer product are not guaranteed.