How to Find the Questions People Ask ChatGPT About Your Business

Can you see the actual questions people ask AI assistants?

No, not directly. ChatGPT, Gemini, Claude and Perplexity do not publish user prompts, and analytics does not receive them. When a visitor clicks through from ChatGPT, you can see that the visit came from ChatGPT and which page they landed on, but not what they asked.

Some tools offer prompt data. A few, such as Profound, use opt-in consumer panels that record real AI conversations, so the wording is genuine but comes from panellists rather than your own buyers, and the volumes are extrapolated; others model prompts from search data or have AI generate them. Use any of them as hints to check against your own customer evidence; see whether AI prompt volume data is reliable. For how ChatGPT turns a question into web searches, see how to use browser tools to reveal ChatGPT's search queries.

Where can you find the real wording people use?

Eight sources, roughly in order of value:

1. Customers themselves. Ask new customers, on forms or calls, whether they used an AI tool while choosing, and what they asked. This is the closest you will get to real prompts.
2. Sales and pre-sale conversations. Questions buyers ask on calls, in demo requests and in chat widgets, written down word for word.
3. Support tickets and chat transcripts. The problems and "can it…?" questions people bring after or just before buying.
4. Search Console long queries. The Performance report includes queries typed into Google's AI Mode where your page appeared, unlabelled, and each follow-up counts as a new query. Very long, question-style queries are close cousins of AI prompts.
5. AI referral landing pages. The pages ChatGPT and other assistants send visitors to show which topics bring people to you.
6. Reviews and community discussions. How customers describe the problem they were solving and what mattered in their choice.
7. Bing Webmaster Tools AI Performance. Its grounding queries show the search phrases Copilot and Bing's AI answers used when they retrieved and cited your pages. They are the engine's rewritten searches, not users' prompts, but they reveal the topics and conditions that bring AI answers to your site.
8. "People also ask" and autocomplete. Common phrasings of related questions, useful for filling gaps.

How do you mine Search Console for AI-style questions?

Search Console's performance report lets you filter queries with a custom regular expression. Two filters are especially useful:

• Question starts: a filter such as ^(who|what|which|where|when|why|how|can|should|is|are|does|do)\b shows queries written as questions.
• Long queries: a filter such as ^(\S+\s+){7,}\S+$ shows queries of eight words or more.

Export the results for the last three to six months and group them by need. Long, specific searches like "which accounting software works for a UK charity with volunteers" are phrased much like AI prompts, and the same people often ask both. They also show the conditions buyers add, such as sector, size, location and budget.

How do you ask customers what they asked AI?

Make it part of normal processes:

• Onboarding or order forms: add "Did you use an AI assistant, such as ChatGPT, while choosing us? If so, what did you ask?" as an optional free-text question.
• Sales calls: ask early, "How did you start looking for a solution like ours?" and note any mention of AI tools and the wording used.
• "How did you hear about us?": add AI assistants as an option, with a follow-up box.

Even a few dozen answers reveal patterns: the conditions buyers mention, the competitors they were shown, and the terms they used. Record the wording exactly; paraphrasing loses the value.

How do you find the questions your ideal customer asks AI?

Start from who buys, then what triggers their search:

• List the situations that make your ideal customer start looking, such as a new hire, a failed tool, a deadline or a price rise.
• For each situation, write the question they would ask, in their words, with the conditions they would include.
• Check each against evidence from the sources above. Keep questions that appear in customer, sales or search data; treat the rest as hypotheses.
• Cover the buying committee in B2B: finance, technical, end users and procurement each ask different questions.

Using AI to brainstorm variations is fine, as long as each question is checked against real evidence before you rely on it. A fuller method for choosing and scoring questions is in how to choose the right prompts to track.

How do you work out the questions potential patients ask AI?

Healthcare adds two differences: patients often start from symptoms rather than services, and privacy rules limit what you can use.

• Start from symptoms and concerns: "Why does my knee click when I climb stairs?", "Is laser eye surgery safe if I have dry eyes?"
• Move to treatment and provider questions: "Where can I get a knee assessment in [town] without a GP referral?", "Which clinics offer [treatment] and take [insurer]?"
• Include practical and emotional questions: cost, waiting times, recovery, fear of pain, what happens at the first appointment.
• Use de-identified sources only: categories of reasons for visit, common questions reception staff hear, and anonymised FAQ logs. Never use identifiable patient information, and never paste it into AI tools.

Clinicians and front-desk staff are often the best source: ask them for the ten questions they hear most, word for word.

How do you turn the findings into a question list?

1. Pool everything into one sheet: the exact wording and where it came from.
2. Group by need, merging different phrasings of the same question.
3. Count sources per need. Needs that appear in several sources are the strongest.
4. Write one representative question per need, keeping the buyer's words and conditions.
5. Split into groups: questions without your name (visibility), with your name (accuracy), and comparisons with named rivals.
6. Track 20–40 of them in AI engines with repeated runs, and use the rest as content ideas.

Then check how ChatGPT actually answers them; see how to check whether ChatGPT recommends your business.

How often should you refresh the question list?

Review it every quarter against new sales, support and Search Console data. Add questions that start appearing, retire ones that no longer come up, and record every change so tracking trends remain comparable. Refresh sooner after a launch, a price change or the arrival of a new competitor, since each tends to create new questions quickly. Keep retired questions in an archive tab with their history; they are often worth re-checking a year later, when the market has moved on.

What do people ask about finding AI questions?

Can ChatGPT tell me what people ask about my business?

It can suggest plausible questions, but it has no access to other users' conversations. Treat its suggestions as ideas to check against real evidence.

Do AI referrals in analytics show the prompt that was used?

No. They show the source and the landing page. Some links carry parameters that identify the source, but not the question.

Are Google search queries a good proxy for AI prompts?

For long, question-style queries, reasonably good. Short keyword searches are a weaker guide, because AI prompts tend to be longer and more conversational.

How many real customer answers do I need?

Thirty to fifty verbatim answers about how customers searched usually reveal the main patterns for one market.