We ran our own tool on ourselves.
Every vendor in this category will show you a dashboard. Almost none will show you theirs. This page reads our live measurement data, and it stays up whether or not the number is flattering.
2026-07-21 to 2026-09-28. Updated automatically from the same table the product writes to.
By engine
| Engine | Checks | Mentions |
|---|---|---|
| Claude | 67 | 0 |
| ChatGPT | 7 | 0 |
| Gemini | 6 | 0 |
| Perplexity | 1 | 0 |
The mix is uneven, which limits what a later comparison can claim. Per-engine rates are the only fair read, and the engines with a handful of checks cannot support a claim at all. We would rather publish that caveat than a blended number that hides it.
The questions we measure
Fixed before we started and unchanged since. Changing the questions mid-study is how a flat result becomes a chart that goes up.
- “what's the best way to improve visibility in AI chatbot answers”
- “What's the best way to improve visibility in ChatGPT and Claude search results?”
Why publish this
Because the alternative is asking you to trust a number you cannot check. We have no client logos to show you and no case study yet, and inventing one would be the same dishonesty we warn about in how to evaluate AI visibility tools.
One thing this page would have got wrong if we had built it earlier: our scoring once counted a model replying “I’m not familiar with that brand” as a mention, because the sentence contains the brand name. That inflated two reports to 100% and 75%. It is fixed, and it is the first question worth asking any vendor here, us included.
A flat result is a real finding. If this number never moves, the useful thing is knowing why.