AI Visibility Checker — And What “AI Overview Checkers” Cannot Tell You
Type “AI overview checker” into a search engine and you will find a row of tools promising to tell you, instantly, whether your site appears in Google’s AI Overviews. Almost...
Type “AI overview checker” into a search engine and you will find a row of tools promising to tell you, instantly, whether your site appears in Google’s AI Overviews. Almost none of them can do that. This page explains what is actually checkable, gives you a real check on the surface we can query, and shows you how to verify the rest by hand.
Run the check
Five buyer-style prompts, none containing your brand name. You get the raw answers back, not just a score. Three checks per day.
What this tool measures, precisely
It sends five buyer-style prompts to a generative model through its API. None of the prompts contain your brand name — that is the whole point. If a prompt says “what do you think of Acme?”, the answer only tells you the model has heard of Acme. The useful question is whether the model brings you up when a buyer describes their problem.
| Metric | Definition | What a low score tells you |
|---|---|---|
| Mention Rate | Share of answers in which your brand name appears | The model does not associate you with the category. This is a third-party coverage problem, not an on-page one. |
| Citation Rate | Share of answers in which your domain appears as a source | Your pages are not being treated as citable. This is a content-structure and authority problem. |
| Raw answers | The full text of every response | So you can check our scoring rather than take it on trust. |
What this tool does not measure — stated plainly
It does not check Google AI Overviews. It does not check ChatGPT, Perplexity or Copilot. Those are separate surfaces with separate retrieval behaviour, and a result on one is not a result on another. Any tool that shows you a single “AI visibility score” without naming the engines behind it is averaging things that do not average.
Why an honest instant “AI Overview checker” is hard to build
| Obstacle | Why it matters |
|---|---|
| AI Overviews are not served through a public API | There is no sanctioned way to query them at scale, so tools scrape — which is fragile and against the terms of the surface they scrape. |
| They are personalised and location-dependent | The same query produces different results by country, device and history. A single check is one sample, not a fact. |
| They do not trigger on every query | Whether an Overview appears at all varies by query type and changes over time, so “not found” is ambiguous. |
| Results shift without notice | A checker that ran last month is not comparable to one that runs today unless the prompt set and method were frozen. |
None of that makes AI Overviews unmeasurable — it makes them measurable only with browser-based collection, a fixed query set, and repeated sampling. That is slow and it is not instant. We would rather say so than sell you a number we cannot defend.
How to check AI Overviews yourself, by hand
- Pick ten queries a buyer would actually type. No brand names.
- Run each in a clean browser session, with location set to your target market.
- Record three things per query: whether an AI Overview appeared, whether your brand is named in it, and which domains are linked as sources.
- Repeat the same ten queries on the same day each month. Comparability comes from not changing the test.
- Cross-check against Search Console: filter impressions by those queries and watch for impressions rising while clicks stay flat — a common signature of being summarised rather than clicked.
Ten queries checked properly once a month beats a dashboard number you cannot audit.
What to do with a 0% result
It is more common than vendors admit, and it is useful precisely because it is unambiguous. Our own first baseline scored our brand at 0% on both mention and citation, and the model named three competitors instead. The work that follows splits cleanly:
- Mention is the problem → the fix is off-site: consistent entity information everywhere you appear, presence in the listings and publications that cover your category, and coverage worth citing.
- Citation is the problem → the fix is on-site: restructure your best pages into self-contained, sourced claims with dates, tables and question-shaped headings.
- Both are zero → start with eligibility. Confirm your robots rules do not block AI crawlers and that your key pages render server-side. That check takes an hour and occasionally explains the whole result.
Related reading
- How to measure AI search visibility — the full method, reproducible by anyone.
- Why you are not appearing in AI Overviews
- How brands get cited by ChatGPT
- AI search optimisation — scope, method and pricing.
Frequently asked questions
Does this check Google AI Overviews?
No. It queries a generative model through its API. AI Overviews are a different surface that requires browser-based collection — the section above explains how to check them by hand.
Why are there only five prompts?
Because it is free and each prompt is a live model call. Five gives you a directional read. A defensible baseline needs 50 or more, which is what we run in a paid engagement.
Is a 0% result bad?
It is normal for a brand with little third-party coverage, and it is honest. Our own first measurement was 0% on both metrics.
Can I see how you score it?
Yes — the raw answers are returned with every check so you can verify the matching yourself. Brand matching is done on word boundaries with accents normalised, so a short brand name cannot match inside a longer unrelated word.
Why three checks per day?
Each check costs five model calls. The cap keeps the tool free and available. If you need more, get in touch.
Want the full baseline instead of five prompts?
We run 50–100 prompts across the engines in scope, score Mention Rate, Citation Rate and Share of Model, and hand you the competitor board plus every raw answer.
Need an SEO, AEO or GEO strategy?
The Vidco Group team is ready to work with you