Broad product queries cite listicles, not the brands in them
Summary
A practitioner's log of broad category prompts in AI search is useful for the domains it names, not for the fact that their own brand went uncited. Those pages are where the buying language for a category gets written.
Run the prompts in two passes, broad category terms and then terms naming the product, and treat a zero on the broad pass as work to do on other people's pages.
Three broad product-category queries run through AI search returned zero citations for the tester’s own brand, and the answers came back built on listicles. The r/TechSEO thread, posted by u/SoloDevLucas, who ran the test and logged which domains each answer leaned on, reports the brand’s result as nothing at all. The poster says the full cited-domain tables are published off the thread.
The zero is the least interesting number in that log. A citation record for a category query names the three to five pages an assistant actually answers from, and on a broad query those pages are listicles written by someone else. The poster’s argument in the thread is that the recommendation language gets written on those same pages, so knowing which ones the answer leans on shows where to start.
u/BoGrumpus, a commenter in the thread, reads the listicles as a signal about the query rather than about the brand. A term broad enough to return roundups is one the system is still using to help a buyer narrow down, on that reading, and it is not yet recommending a final choice. The same comment puts Google behind Bing and ChatGPT in how soon either will name specific brands and product lines, and treats being cited as only the first step, with what the citing pages recommend mattering more than whether the brand is in them.
Both readings hold, and they measure different things. A broad category query measures the listicle set, not the brand’s standing in AI answers. The likelier explanation for a zero there is a placement gap on third-party pages, not an assistant that cannot see the site. Neither comment says so, but the test is more useful run in two passes: the broad category prompts, then prompts that name the product or the specific job it does. A query that names a brand behaves differently, and ChatGPT searches the brand’s own domain directly on some of them, so a zero on that second pass is the one worth worrying about.
What to do
- Log the cited URL for every prompt, not just whether the brand appears. The list of pages is the deliverable.
- Sort those pages by whether they can be influenced: a roundup that takes review pitches, a comparison page with wrong specs to correct, a thread where the product is simply missing.
- Repeat the prompts across more than one assistant, and on a paid tier as well as the default, since ChatGPT’s default model cites brand sites far less than its Thinking model.
- Read what each cited page says about the category, not only whether the brand is named in it. A page can cite the brand and still send the buyer to a competitor.