Does ChatGPT recommend you for [category]? How to measure without a $399 tool
When a buyer types "best [category] tool for [ICP]" into ChatGPT, does your product come up? That question now has an entire category of dashboards selling you the continuous version of the answer. The category anchor on our radar is Vismore: $99/month at entry, $399/month at its Advanced tier (vendor pricing pages, re-verified 2026-09-13; check again before you quote it). Budget tiers sit far below that: Otterly's entry plan is $29/month (re-verified 2026-09-13).
Here's the thing though: the first version of the answer costs you one browser tab and half an hour. You should have that answer before you pay anyone for the continuous version.
The 30-minute version
Open a fresh chat and ask the question the way a buyer would. Not "generative engine optimization platform". For my product the buyer query is "best weekly AI citation tracker for a small B2B SaaS team". If you sell to accountants, ask like an accountant. If you sell to landscapers, ask like a landscaper with two crews and a scheduling problem.
Then read the answer with two questions in mind:
- Were you named?
- If not, who or what was cited instead?
The second answer is the one people skip, and it's the more useful one. The list the model produces instead of you is your real competitive set. In my own category checks so far the named alternatives have been listicles and comparison posts more often than the products my positioning page worries about (hypothesis from a handful of informal runs, not a measured sample).
Write down date, query, engine, named Y/N, and cited-instead domain. Five columns in a spreadsheet. That spreadsheet is the whole instrument. A $399 dashboard is, at its top line, a prettier and more continuous version of those five columns plus some alerting.
One run is an anecdote
LLM answers are non-deterministic. Ask the same question twice and you can get two different brand lists, which is exactly why "I asked once and I'm in there" is not a finding. My working rule is 3-5 runs per query per week and recording the majority answer. That's a hypothesis about a usable cadence, not a validated method; the weekly cohorts we're running are what will tell me whether mention frequency over N runs actually tracks anything a buyer sees.
The weekly rhythm matters for a second reason. You can't change the model directly. You publish something, wait, and re-probe. The feedback loop is a week long no matter how often you check, so daily anxiety buys you nothing that a weekly grid doesn't.
What the grid can't tell you
Being named is a binary, and binary metrics flatter you. "You're mentioned" covers both "the cheap alternative to Y" and "the category standard". Only one of those framings helps you, and no citation tracker I've seen scores framing (if yours does, I want to see the methodology).
The grid also measures the logged-out, default-model answer. A buyer with chat history and different settings can see something else entirely. Treat your grid as the baseline case, not the buyer's exact experience.
And a good mention rate doesn't tell you what to do next. That comes from reading the sources the answer leans on: which comparison pages, which listicles, which threads. The fix for a weak result is almost always one publishable artifact, like an honest comparison page or a tested-it-myself post. That's a content task with a weekly cadence, not a dashboard subscription.
If the result is bad
Bad result, meaning you're absent and a competitor is named: read the sources behind the answer and publish the artifact they'd cite. A comparison page is the highest-yield start because it's the artifact buyers' questions map onto. Then re-probe next week and see if the answer moved. If it didn't after a few honest attempts, you've learned something about how far content alone gets you in your category, which is worth knowing before you rent a $399 dashboard to watch it.
The free check
That five-column grid is exactly what CiteWeek runs for you weekly: three buyer-language queries across ChatGPT, Perplexity and Google AI Overviews, one email with named/cited-instead, and one article worth publishing. The free check runs the grid once so you can see the shape of the data before paying for anything. It's 3 checks per email per 14 days, no card, results on the page:
When you repost or syndicate this, set utm_source to wherever it ran and keep utm_campaign as article-1-does-chatgpt-recommend-you. That's how signups get attributed back to this article in the funnel table, and I'd rather learn which articles work from tagged links than from vibes.