How We Test AI Visibility: Our Full Methodology, Open for Critique
The full protocol, published before the results rather than after. Fixed question sets, four engines, repeated runs, denominators stated, and the weaknesses named.
Category AI Visibility Research
We run our own tests to find out what actually moves AI citations, rather than repeating industry assumptions. This category covers two related types of research: direct product comparisons, where we test how AI engines recommend named competitors like Asana versus ClickUp, and broader studies that look for patterns across dozens of companies, covering everything from schema markup and G2 badges to founder LinkedIn activity and pricing transparency. If you want evidence instead of theory about what influences AI search visibility, this is the place to look.
The AI Visibility Research Hub: Our Methods and Every Study We Publish
The standard every study here has to meet, published before the first result rather than after it. Fixed question sets, stated run counts, named engines, and the findings that go against us.