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Nearly every statistic you read about AI search is a summary. A vendor runs some prompts, publishes a percentage, and you have to take their word for it — the runs themselves are never shown. That is not a knock on the numbers; it just means nobody outside the company can check them.

We do it the other way round. Everything below is hand-run, and the per-run data is published here in full — every question, every engine, every brand it named and every source it cited. If you think we read it wrong, you can open the file and say so.

4 studies · 129 logged runs · 4 engines. All United States, English, B2B-SaaS buyer questions. Every figure comes from a run we actually made — nothing is modeled, estimated or extrapolated.

The current finding

In August 2026 we asked ChatGPT, Perplexity, Gemini and Google's AI Overview the same twelve buyer questions and logged both the sources each cited and the brands each recommended. Across the seven open-ended recommendation questions all four answered:

QuestionBrands all four namedBrand overlapSources all four citedSource overlap
best CRM for startupsHubSpot, Pipedrive22%none0%
best project management softwareAsana, ClickUp, Trello38%zapier.com, project-management.com6%
best email marketing platformActiveCampaign, Kit25%none0%
best AI writing toolsChatGPT, Claude25%none0%
Salesforce alternativesHubSpot, Pipedrive, Zoho, MS Dynamics36%none0%
cheaper alternatives to HubSpotZoho, Pipedrive, EngageBay30%none0%
best free project management toolsTrello, ClickUp, Asana50%none0%
Average32%1%

The four engines agreed on 32% of the brands they recommended and 1% of the sources they cited. All seven questions produced at least one brand every engine named; six of the seven produced no shared source at all. The engines are not reading the same pages, but they arrive at the same shortlist — the full write-up is here.

Download the raw data

All 48 runs from that round — 189 recommended brands and 322 cited sources, one row per engine-question pair. Brands are listed in the order the engine named them; every source carries a type code (vendor site, review media, independent listicle, Reddit, forum, YouTube, reference). Free to reuse under CC BY 4.0.

Download CSV Download JSON

The JSON carries the same rows plus the run conditions, the source-type key and the stated limits, so the file stands on its own if it travels without this page.

What we can and cannot prove

A study that asks you to verify it should also say where verification runs out. For this round:

  • Gemini — all twelve runs have a saved conversation. Re-openable, so every Gemini row can be checked against the original answer.
  • Perplexity — two of twelve. The rest were not saved at the time.
  • ChatGPT — none. Every question ran in a temporary chat, which our method requires so that no memory carries between questions. Temporary chats leave no transcript, so this is the cost of a clean session rather than an oversight — but the effect is the same: the ChatGPT rows rest on our logging alone.
  • Google AI Overview — none. AI Overviews have no permanent URL and can differ between runs.

Two more limits worth stating plainly. Each engine-question pair was run once, so a single run cannot tell a stable pattern from a lucky draw — the 32%-versus-1% gap is wide enough that we doubt it is noise, but the individual per-question percentages are not, and should not be read as precise. And ChatGPT and the AI Overview both hide some sources behind a “+N” badge, so the source counts in the file are a floor, not a total.

From the next round on, every run gets a screenshot saved at collection time. We would rather publish the gap than quietly leave it out.

The studies

Reuse it, or run it yourself

Everything here is CC BY 4.0 — use it, quote it, chart it, argue with it. Attribution we suggest:

Is My Brand in AI (2026). Cross-engine AI citation and brand-recommendation study. https://ismybrandinai.com/research

The exact conditions — question set, engine settings, how a “recommendation” was counted, and why the “X vs Y” questions are excluded from the overlap average — are on the methodology page and in each study. Journalists and researchers who want the working notes can get in touch.