Buyers have started asking ChatGPT and Gemini which software to use instead of opening ten tabs. So over the last few weeks I ran a simple experiment 241 times: for each software category, I asked the assistants the questions a buyer actually types, wrote down every product they named, and wrote down every web page the answer was built from.
The result is 241 category measurements, 1,446 answers read, and 5,037 product mentions, all from real runs I can show you. Three findings surprised me enough to write this.
The method, so you can repeat it
For each category I asked six buyer-style questions: the plain "best X", plus "best free X", "most affordable X", "best X for small teams", "what X should I use", and "X recommendations". Each question got one live web search, put to ChatGPT and Gemini (and Perplexity on the earliest runs). Then I recorded, per answer, every product named and every source domain the assistant cited. No opinions, no model asked to rank anything. Whether a product counts is a literal check for its name in the answer text.
You can do this by hand for your own category in an afternoon. That is the whole point: it is countable, not a vibe.
Finding 1: Reddit runs the shortlist, the review sites you pay for do not
Across the 241 categories, here is how often each kind of source showed up behind an answer:
| Source | In how many of the 241 categories |
|---|---|
| 225 (93%) | |
| Quora | 148 (61%) |
| G2 | 135 (56%) |
| YouTube | 117 (49%) |
| Gartner | 111 (46%) |
| Capterra | 30 (12%) |
Reddit was behind the answers in 93% of categories and fed 1,202 individual answers. Capterra, the directory a lot of software teams pour budget into, was behind 12%. In 196 of the 241 categories, Reddit was a source and Capterra was not there at all.
This is not a Reddit-is-cool take. It is where the assistants actually go. When someone asks "best IT service management software" or "best social media scheduling tools", the answer is stitched from Reddit threads, community Q&A, and independent roundups, not from the review grid you optimized your profile on. You can see it category by category: Reddit fed every one of the six answers in IT service management, fraud detection, threat intelligence, and social media scheduling.
Finding 2: 62% of the time, there is no single winner
We assume AI hands out one confident answer. It mostly does not. In 149 of the 241 categories (62%), no product was named in all of the answers. Change one word in the question and the shortlist reorganizes.
The clearest example is test automation software: eight different tools tied at the top, each named in only two of the six answers. Warehouse management had a six-way tie. Only 38% of categories had a product the assistants named every single time.
For a buyer, this means the "best" answer is less stable than it looks. For a vendor, it means the race is winnable: in most categories nobody owns the top slot, so the gap between being named and being invisible is small.
Finding 3: a few brands are the AI's default across dozens of unrelated categories
Some names show up everywhere. Counting how many distinct categories named each brand:
- HubSpot: 24 categories (from deal desk to help desk to product marketing)
- Salesforce: 16
- Zendesk: 12
- Connecteam: 12
- Rippling: 12
- BambooHR: 11
- Zapier, Datadog, Semrush, monday.com: 10 each
HubSpot gets named by the assistants in revenue operations, sales forecasting, customer self-service, and twenty other categories, whether or not it is the obvious pick. The models reach for the brand they have seen described the most across the web, and that compounds. If you are competing with one of these defaults, you are not competing on features, you are competing on how often your name appears on the pages the assistant reads.
What actually gets you named
Put the three findings together and the mechanism is clear: the source list decides who gets recommended, not market share. The assistant can only name what its live search returns, and its live search returns Reddit, community threads, independent roundups, and sometimes a vendor's own comparison page. Over and over I saw a small product get named once because it sat in the single roundup that answered the "free" question, and a market leader go missing because it was absent from the exact page the assistant pulled.
So if you sell software and want to be in these answers:
- Be in the Reddit and Quora threads that rank for your category. They were behind 93% and 61% of answers. This is earned, not bought.
- Get into the independent roundups that keep recurring for your category, and keep your G2 entry current (56%). Deprioritize Capterra-only effort (12%).
- Publish your own honest "best X" comparison. A vendor's own page repeatedly became the source the assistant quoted.
- Pick the question you want to win. "Free" and "affordable" pull completely different shortlists than the plain "best", so a budget product can own a query the leaders never appear in.
See your own category
I put all 241 measurements up, one page each, with the full named list, the counts, and the source map behind every answer: glotier.com/guides/who-ai-recommends.
I build Glotier, an affordable AI-visibility tool, so I have skin in this: the same measurement runs on your own category in about a minute, free and with no account, and tells you whether ChatGPT and Gemini name you or a rival, and which exact pages decide it. But the 241 above cost you nothing to read, and the method costs you nothing to repeat. If you sell in a category with real alternatives, run it before your competitor does.
Data: 241 categories measured on ChatGPT and Gemini, six buyer questions each, one live web search per answer, every product and source logged. Happy to share the raw counts for any category.
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