AI search visibility
AI search visibility is how often answer engines — ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews — mention your brand and cite your pages when someone asks a question in your category. Unlike search rankings, there is no public scoreboard, so it has to be measured by probing the models directly and repeatedly.
Why rankings no longer tell you the whole story
A growing share of commercial questions never produce a click. The buyer asks an assistant, reads a synthesised answer, and either remembers three brand names or does not. If you are not one of those three, you were never in the consideration set, and no ranking report will tell you that happened.
This is why impressions can stay flat while a category quietly reallocates demand. The traffic you lose to answer engines does not show up as a ranking drop — it shows up as fewer sessions at the same position.
The three metrics worth tracking
Most tools report one number. Three are needed to act:
- Mention rate — the share of probe questions where your brand name appears in the answer at all. This measures whether the model knows you exist.
- Citation rate — the share where your own URL is listed as a source. This measures whether your pages are retrievable and quotable, not just whether the model has memorised your name.
- Leakage — which competitor took the slot when you were omitted, and for which question. This is the single most actionable number, because it names the page you need to write.
Building a probe set that means something
Write 20 to 40 questions the way a buyer would type them, not the way a marketer would. Include category questions ('best tool for X'), comparison questions ('X vs Y'), problem questions ('how do I stop Z happening'), and one or two direct brand questions as a control.
Run the same set on the same schedule — weekly is enough — against every model that matters to you. Never change the questions mid-experiment, or you lose the trend. Record the full answer text, not just yes/no, so you can see how you were described when you were mentioned.
What actually moves the numbers
In order of observed impact: fixing entity confusion (the model mixing you up with a similarly named company), making pages crawlable as plain HTML, adding answer-first blocks with checkable facts, publishing genuinely comparative content that names competitors honestly, and getting mentioned on third-party pages the models already retrieve.
What does not reliably move them: keyword density, publishing volume without structure, and adding schema to a page with nothing quotable in it.
Frequently asked questions
How is AI search visibility different from share of voice?
Share of voice measures mentions across media. AI search visibility measures mentions and citations inside generated answers to specific buying questions, which maps far more directly to demand.
How often should I probe?
Weekly is enough for most categories. Daily adds noise without adding signal, because model answers vary run to run.
Do AI Overviews count?
Yes, and they are worth tracking separately. Google AI Overviews draw on the classic index heavily, so they respond faster to conventional SEO fixes than ChatGPT does.
Related guides
- How to rank in ChatGPT — ChatGPT does not rank pages, it picks sources to cite. Here is what makes a page citable, how to measure it, and the fixes that change the answer.
- AEO vs SEO vs GEO — SEO wins rankings, AEO wins the answer, GEO wins the citation. What each term actually means, how they overlap, and how to measure all three.
- Why AI doesn't mention your brand — Six concrete reasons ChatGPT and Perplexity skip your brand, how to tell which one applies to you, and the fix for each.