
AI Visibility research, inside Ghostart Labs: why we publish research that could prove us wrong
If you're trying to work out whether your business shows up when someone asks ChatGPT "who's good at this?", you're stuck with a problem: almost nobody selling AI visibility tools has evidence for what they're claiming.

Nigel Jay Cooper
Co-Founder & Chief Storyteller. Literary fiction author and product builder.
That's the gap Ghostart Labs exists to close. Ghostart Labs is a fundamental part of Ghostart. It's how we learn about the AI Visibility industry and what's real and what's snake oil.
The three kinds of study we run:
- Surveys.
A research company asks real business owners a set of questions on our behalf. We never contact anyone ourselves. Respondents come from the research company's own opted-in pool. - Experiments.
We publish carefully matched pieces of content, identical except for the one thing we're testing, then track which version the AI tools actually cite, week after week. - Analyses.
We look for patterns in data we already hold, always anonymised and aggregated. No business or person is ever identifiable in anything we publish.
The rules every study follows:
The question is locked first. We publish what we're testing and how, before collecting any data, so the numbers can't rewrite the question.
Rates, never ranks. Ask an AI the same question three times and you can get three different answers. So we never trust a single sample, every number is measured across repeats, and we show how many.
Every result publishes. A study that finds nothing, or finds against us, goes up with the same prominence as one that flatters us.
Check our work. Methods are stated in enough detail to re-run them, and the raw data is downloadable from every study.
Connect with me on LinkedIn | Ghostart Platform
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