I asked ChatGPT and Gemini 50 questions my buyers ask. My SaaS showed up once.

My product was named in 1 of 50 AI answers. Its biggest competitor was named in 19.

These weren't vanity searches. They were 25 questions a real buyer types before they've heard of any brand, each asked on ChatGPT and on Gemini. Search Console doesn't show what ChatGPT or Gemini say about you, and a rank tracker can't either. So I measured it myself.

Here's what came back, what surprised me, and the code I use to turn a pile of AI answers into numbers you can track.

Disclosure: the product is DropPerch, a domain-expiry monitor I run, and I measured it with CiteGaps, which I also build. All the numbers below are from that one workspace, week of 12 October 2026.

The setup

• 25 buyer questions, written the way people search before they know any brand. For example: "What is the best domain expiry monitoring software for small businesses?"
• No brand names in the questions. "Is DropPerch good?" tells you how an AI describes you, not whether it recommends you.
• Two engines: ChatGPT and Gemini. Collected live, the way a buyer sees them, sources included. I didn't use the bare model API, because without web search it doesn't show what buyers see or which pages it cites.
• One week, 50 answers. For each answer I kept the full text, every brand named, its position, and every cited URL.

The result

One ChatGPT answer to that small-business question listed HetrixTools, UptimeRobot and DomainMOD. DropPerch wasn't in it.

Three things I didn't expect

1. I was cited more often than I was named

DropPerch was named in 2% of answers but linked as a source in 4%. So in at least one answer, the engine used my site as a source and still recommended someone else.

A mention (your brand in the text) and a citation (your URL in the sources) are different signals, and they move separately. Track both.

2. The most-cited source was a competitor's own website

The single most-cited source across the week was domcop.com: 102 citations in 50 answers. DomCop is also on the competitor list, named in 32% of answers.

That changed how I think about the problem. The engines get their shortlist from a handful of pages, and one of those pages is a competitor explaining the category in its own words. If my site and the pages around it don't answer the same questions as clearly, I'm not on the shortlist.

3. A forum thread was doing my competitors' marketing

One answer that named DropCatch, ExpiredDomains.net and DomCop, and not DropPerch, cited a discussion thread recommending DropCatch and ExpiredDomains.net. A thread an AI engine quotes is free marketing for whoever it names. A genuine, disclosed reply there can be worth more than another blog post on my own domain.

The code: turning answers into three numbers

Once you have the answers, you only need three numbers. Here's the scoring logic, simplified from what I run in production:

type Answer = {
  brands: { name: string; position: number }[]; // in the order the answer named them
  citedDomains: string[];                        // e.g. ["domcop.com", "reddit.com"]
};

function score(answers: Answer[], brand: string, domain: string) {
  const key = brand.toLowerCase();
  // Your position in each answer, or null when you weren't named.
  const positions = answers
    .map((a) => a.brands.find((b) => b.name.toLowerCase() === key)?.position ?? null)
    .filter((p): p is number => p !== null);

  const cites = (d: string) => d === domain || d.endsWith(`.${domain}`); // count subdomains too

  return {
    // How often you make the shortlist at all.
    visibilityShare: positions.length / answers.length,
    // How often the engine uses your own site as a source.
    citationShare: answers.filter((a) => a.citedDomains.some(cites)).length / answers.length,
    // Where you appear when you DO appear. Never average in the misses.
    avgPosition: positions.length ? positions.reduce((s, p) => s + p, 0) / positions.length : null,
  };
}

Run the same function for each competitor and you get the table above.

Getting brands out of free text is the fiddly part. I give each answer to an LLM with a strict JSON shape, {"brands":[{"name": string, "sentiment": "positive"|"neutral"|"negative"|"mixed"}]}, and take each brand's position from the order it returns. Sentiment comes for free, and it matters: being named often but described badly is its own problem.

Rules that keep the numbers honest

• Keep the question set fixed week to week. Change the questions and you've changed the measurement.
• Exclude failed answers instead of counting them as "not named".
• Mind the sample size. With 50 answers, one answer is 2 percentage points. A 3-point jump can be noise.
• Read the trend, not the week. AI answers change from one session to the next. One week is a sample, not a verdict.

Bonus: see ChatGPT's clicks in your analytics

When ChatGPT links to a page, it adds utm_source=chatgpt.com to the URL. That's from OpenAI's publisher FAQ. In GA4, look under Reports → Acquisition → Traffic acquisition for chatgpt.com as a source. If your visibility share rises but those visits don't, the answers mention you without linking to you.

What I'm doing about it

Nothing clever. Just the list the data gave me:

1. Get onto the third-party pages the engines already cite: the directories, comparison lists and threads in the sources, before any new content of my own.
2. Answer the exact questions I'm missing. A page per lost question, with the specifics a buyer needs, not a generic "features" page.
3. A comparison page against the brand at 38%, because a buyer comparing tools asks exactly that question.
4. Reply, with disclosure, in the threads that get cited.
5. Re-run the same 50 answers every week and watch the trend.

I'll post the follow-up when there's a trend worth showing, good or bad.

Try it on your own product

You can do all of this by hand with a spreadsheet: write 25 buyer questions, ask each one in a fresh chat, and log who's named and what's cited. Reading 50 answers a week gets old fast, which is why I automated it.

If you want a quick look first, there's a free check: one question, live answers from ChatGPT and Gemini, no sign-up. I also wrote up what each of these metrics means and how to read them together.

Have you checked what ChatGPT says when someone asks for a tool like yours? I'm curious whether anyone else is getting cited without being named. Tell me in the comments.