AI Visibility
What it tells you
More buyers now open an assistant instead of a search box, and the answer they get names a few vendors and quietly leaves out the rest. AI Visibility is where you find out whether you’re in that answer — and, if you’re not, who’s being handed the recommendation instead.
It comes down to three plain readings, tracked over time and worked out the same way for you and for every competitor, so the comparison is fair:
| What you see | What it means |
|---|---|
| AI Visibility Score | One number from 0–100 for how often and how high AI names you. The headline you watch. |
| Mention rate | How often you come up at all when buyers ask. |
| Average rank | When you do come up, how near the top of the answer you land. |
Keeping them apart is the point: being named in every answer but always last is a very different problem from being named rarely but first, and one number alone can’t tell them apart.
What a check looks like
A check puts the same three buyer questions to all three engines — nine answers in all — and reads each one for the brands it names, where they land, and how warmly they’re described. One run reads something like this:
Because the same questions run on every engine, you can see where a gap actually comes from — a brand can lead on one model and go missing on another, and that shows up plainly rather than washing out in an average.
You see the whole field, not just your list
You hand CompetLab a short list of competitors to watch. AI names many more. Every check records every brand the engines bring up — the incumbents they cite by reflex, adjacent tools, and newcomers gaining ground — so you find out who’s genuinely being recommended in your space, including rivals you’d never have thought to add. The field tends to widen as you accumulate checks: when the engines start naming a new player, it turns up here first. Your own domain sits in that same discovered list, measured exactly as everyone else is.
The score you watch
The AI Visibility Score is one number from 0 to 100 — higher is better — that blends how often AI names you with how high it ranks you. Because it’s worked out the same way for every brand, the figure that really matters is the gap: how far you sit behind the name AI recommends most.
It’s a single score across all three engines — there’s no separate per-engine number, so for an engine-by-engine read you look at your rank on each. How the score is put together, and where its limits are, live on the methodology page.
Beyond the score: how AI talks about you
A rank tells you where you landed; AI Visibility also reads how each engine talked about you. Every mention is tagged for how favorably you were treated and for the role you played in the answer:
From everything the engines say, CompetLab also builds an AI Perception profile for each brand — how AI frames its positioning, strengths, and differentiation — read back from the answers themselves rather than the brand’s own website. For the competitor AI recommends most, you get a plain-language read on why it’s winning and what to do about it.
A trend, not a snapshot
AI answers wander from one day to the next, so no single check is the whole truth. CompetLab runs on a schedule and keeps every result, so what you actually read is the direction over many checks — charted by score or mention rate across 30 days, 90 days, or all time.
You can also tune the questions a check asks to match how your buyers really talk. Change one and your history stays intact: a marker drops onto the chart exactly where the wording changed, so a shift you can explain never gets mistaken for one you can’t.
AI Visibility runs on its own cadence — anywhere from daily to monthly, set independently of the other dimensions. Turning it on, choosing the frequency, and editing the questions are all covered in How monitoring works.
Work with it in code
Everything quantitative here is available programmatically — the same data the dashboards render.
FAQ
What is AI Visibility?
AI Visibility is one of CompetLab's five continuously monitored dimensions. It tells you how the major AI assistants — ChatGPT, Claude, and Gemini — answer when a buyer asks for a recommendation in your space: whether they name you, how often, and how high up, versus every competitor they surface. Each check puts the same set of buyer questions to all three engines, reads the answers for who's named and in what order, and rolls that into three readings per brand — a score, a mention rate, and an average rank — worked out the same way for you and your rivals so the gap is fair to read. Because it's monitored, every check is kept as history and can raise alerts between briefings.
Which AI engines does it check?
Three: ChatGPT (from OpenAI), Claude (from Anthropic), and Gemini (from Google). Every check runs your questions across all three, and the results are shown both per engine and as one combined score, so you can tell whether a gap is everywhere or specific to one model. CompetLab names only the engines it actually queries — it doesn't measure search-engine AI overviews or other assistants, and it doesn't try to model how one person's location or history might change a reply. Because these assistants personalize and localize their answers, what a check captures is a steady, repeatable sample rather than a promise of exactly what any single person sees on a given day.
Does it only track the competitors I add?
No — it discovers them. Every check records each brand the engines actually name, not just the competitors you added to the project, so a single run routinely surfaces rivals you never listed: incumbents the models cite by default, adjacent tools, and newcomers gaining ground. That's much of the value — AI Visibility tells you who the engines are putting in front of your buyers, which isn't always the set you thought you were competing with. The discovered field tends to widen over time, and your own brand is measured inside that same list, exactly as everyone else is, so nothing is graded on a different curve.
What is the AI Visibility Score, and is there one per engine?
The AI Visibility Score is a single number from 0 to 100 — higher is better — that blends how often AI names you with how high it ranks you. It's one combined figure across all three engines; there is no separate per-engine score. Mention rate and rank, on the other hand, are broken out per engine, so if you want to compare ChatGPT to Gemini you read those. The score is computed the same way for you and every competitor, which is why the number that usually matters is the gap between you and the brand AI recommends most. How the score is composed, and its honest limits, are on the methodology page.
How is this different from SEO rank tracking?
A rank tracker tells you where your page sits on a results page for a keyword. AI Visibility tells you whether an assistant actually recommends you when a buyer asks — a different question, because the assistant returns a short list of names, not ten blue links, and most of your buyers never see the ones it leaves out. It also goes past position: it reads how favorably each engine talks about you, discovers the whole field of brands being recommended, and tracks the gap to the leader over time. It's built for the way buyers research now — asking an assistant — rather than for classic search rankings.
How often does it run, and can I change the questions?
AI Visibility runs on a schedule you set, anywhere from daily to monthly, and it defaults to weekly. Each monitored dimension keeps its own cadence, so AI Visibility can run more or less often than the others. The questions a check asks are yours to edit — tune them to match how your buyers actually phrase things — and editing them never wipes your history: the change takes effect on the next run and is marked on the trend chart so past and present stay comparable. You set the frequency and edit the questions in the project's settings; see How monitoring works for the full walkthrough.