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ChatGPT mentions us in 58% of answers and recommends us in 0%. The gap between being seen and being chosen is where AI search is won, and almost nobody measures it.
We ran our own measurement tool on ourselves. ChatGPT mentioned us in 58% of answers to real buyer questions. It recommended us in 0% of them.
If you had asked us before the test, we would have guessed the two numbers moved together. They do not. And the gap between them is where most businesses are quietly losing customers right now.
When an AI answer mentions your brand, you appear as part of the landscape. Tools in this space include X, Y and Z. It is name recognition, and it is worth something. But the person asking did not ask for a landscape. They asked what they should use.
A mention puts you in the answer. It does not put you in the decision.
A recommendation is the AI answering the actual question: for your situation, use this one. That is the line that moves a buyer. When ChatGPT or Perplexity names one product as the thing to try, a meaningful share of people simply do that. No comparison shopping, no page two, no ten open tabs.
Classic search sent people to a results page and let them decide. AI search increasingly decides first and explains itself second. Being the recommendation is the new ranking first, except there is usually only one spot.
| Mentioned | Recommended | |
|---|---|---|
| Where you appear | Part of the list | The verdict |
| What the buyer does next | Keeps reading | Acts on it |
| Who measures it | A few tools | Almost nobody |
In our own audit, the pattern was clear once we read the actual AI answers rather than the scores. We showed up on brand queries, where someone already knew our name. We disappeared on discovery queries, where someone described a problem and asked what solves it.
AI engines recommend brands they can attach to a specific need, backed by sources they trust: comparison pages, reviews, structured descriptions of who a product serves and when it is the right choice. If that evidence is thin, you get mentioned as a name and skipped as an answer.
Ask an AI engine the questions your buyers actually ask. Not what is your brand, but what should I use for the problem you solve. Do it several times, because answers vary run to run. Note two separate things: whether you appear at all, and whether you are the one being recommended.
Most businesses have never done this once. The ones that do usually find a version of our own result: present in the conversation, absent from the verdict. That gap is measurable, and it is fixable. But only if you know it is there.
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When a buyer asks an AI one question, the engine quietly turns it into about ten. Seer Interactive measured 10.7 hidden sub-queries per prompt across 501 prompts on Gemini 3. Most sites answer the headline question and none of the ten. Here is how to find your gaps.
WeiterlesenThe same question, same engine, same day can produce different answers. That is the nature of AI search, not a bug. The 3 rules we use to avoid showing you fake statistics, and how to read a visibility score without fooling yourself.
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