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How-to guide

How to Find the Questions People Ask ChatGPT About Your Industry

By Rahil Jain, founder of Chalk LabsUpdated How we research

The short answer

Nobody outside the AI companies can see every question people type into ChatGPT, so you build a close picture from first-hand sources. Start with sales calls and support messages, add Search Console and Bing AI Performance data, then check forums and AI follow-up suggestions. Cluster what you find into a list of 30 to 50 prompts.

  • Your own customers are the best source: sales calls, support tickets and onboarding questions use the exact words buyers use.
  • Bing's AI Performance report shows grounding queries, the phrases an AI used to find pages it later cited. Microsoft says it is a sample.
  • Google's Search Console now reports impressions in AI Overviews and AI Mode by page, though not the questions behind them.
  • Treat every list you build as a sample. Re-run it monthly and keep only questions that tie to something you sell.

Can you see the real questions people ask ChatGPT?

No, not in full. We found no public tool or report from OpenAI that lists what users type about your industry, so every method below produces a sample, not a census.

What you can do is combine several imperfect sources until the same questions keep appearing. A question that shows up in sales calls, in Search Console and in a forum thread is almost certainly worth a page.

One study of ChatGPT use found that Practical Guidance, Seeking Information and Writing were the three most common conversation topics, together close to 80% of conversations 1. The study does not state its sample size, so read it as a hint: people use ChatGPT heavily for advice and information, which suggests buyers may too. The study covers consumer use in general, not buying questions.

Do it step by step

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  1. Open your last ten call recordings or notes. Copy every real question into the sheet, in the buyer's own words, and tag the buyer stage: learning, comparing or ready to buy.

    Tip: If you do not record calls, ask each salesperson for their top five repeat questions.

  2. Export the last fifty support emails or chat transcripts. Pull the opening question from each one and merge duplicates. Mark the ones asked more than three times.

  3. In Search Console, open Performance, then Search results, then add a Query filter set to 'Custom (regex)'. Paste the question regex from the templates. Export the rows and add them to the sheet, with the page that received the impressions.

  4. Check the generative AI performance report for the pages that earn impressions in AI Overviews and AI Mode. Note which topics those pages cover, so you can write nearby questions.

    Tip: The report shows impressions only. Do not read it as a click count.

  5. In Bing Webmaster Tools, open AI Performance and export the grounding queries. Add any that match your offer. If your site has too little data, skip this step and repeat it later.

  6. Ask two or three AI assistants your main buyer question. Write down the suggested follow-ups and the sub-topics each answer covers, then run the same prompt in the Query Fan-Out Explorer to see the searches behind it.

  7. Search the subreddit or forum for your core topic. Copy the thread titles that are phrased as questions and note what the best reply left out. Read and record; do not post yet.

  8. Group near-duplicates under one master question. Score each cluster 1 to 3 on frequency, closeness to a sale and whether you can answer it better than current results. Take the ten highest totals as your first pages.

    Tip: Keep a source column. A question backed by three sources beats one backed by one.

Your ticks are saved in this browser only.

Copy-ready templates

Question sheet columns (paste into a spreadsheet header row)

text
question	source	buyer_stage	times_seen	price_or_trust_related	page_that_should_answer	score_1_to_9

Tab-separated so it pastes into separate columns in Google Sheets or Excel.

Search Console regex: question and intent-style queries (starts with a question word, best, cost or price)

regex
^(who|what|when|where|why|how|which|can|does|do|is|are|should|will|best|cost|price)\b

Use with Query, Custom (regex), Matches regex. Search Console uses RE2 syntax, which supports this pattern.

Search Console regex: long conversational queries (8 or more words)

regex
([^ ]* ){7,}[^ ]*

Long queries are closer to how people type into AI assistants. This is our assumption, not a published rule.

Prompts to ask an AI assistant about your own field

text
I run a [business type] in [place]. List 15 questions a first-time buyer would ask before choosing a provider.
What do buyers ask after 'how much does [service] cost'?
What are the most common worries about [service]?
What should I compare when choosing between [option A] and [option B]?

AI-generated questions are guesses. Keep only those that also appear in a real source.

What do you need, and how long does it take?

Budget one focused afternoon for a first list and about an hour a month to refresh it. These times are a rough guess from us, not measured.

You need read access to your Google Search Console property, a Bing Webmaster Tools account, a spreadsheet, and ten minutes with whoever talks to customers most. A free account on any AI assistant helps for the follow-up step.

  • Search Console, which is Google's free report on how your site appears in search.
  • Bing Webmaster Tools, Microsoft's equivalent, which now includes an AI Performance report.
  • A shared sheet with columns for question, source, buyer stage and the page that should answer it.

Why do the exact words of the question matter?

An AI assistant does not search for your one-line keyword. It often turns a question into several smaller searches, which is called query fan-out (see what is query fan-out). Google says AI Overviews and AI Mode may use this technique, issuing multiple related searches across subtopics and data sources 2.

Ahrefs studied 66.6 million logged-out ChatGPT responses from August and September 2026. Only 14.4% contained fan-out queries (web searches), and those averaged about 1.6 fan-out queries each 3. So many questions get answered from the model's memory, and the ones that do search are short bursts of specific phrases.

Those phrases lean towards buying words. In the same study, 'price' rose from 6.0% to 8.9% of fan-out queries between August and September, and 'official' appeared in 13.1% of English ones 3. Questions about cost, reviews and official facts are where a business page can be quoted.

How do sales calls and support logs reveal the best questions?

Customer conversations are the strongest source because they are real, specific and tied to money. Pull ten recent sales calls, the last fifty support emails and your chat transcripts. Highlight every sentence that starts as a question or hides one, such as 'we're not sure if it works with our old system'.

Keep the customer's wording. 'Will this break our billing?' is a better target than 'billing integration compatibility', because the first is how a person types into an assistant.

Add the questions your team answers on every call. A question that costs you the same five minutes each time is a page waiting to be written. Our guide on turning customer calls into pages AI cites covers the page side.

Before and after: cleaning a raw call note
  • Raw note: 'Prospect worried it takes too long and costs more than agency B.'
  • Question 1: How long does [service] take to show results?
  • Question 2: How much does [service] cost compared with [competitor type]?
  • Question 3: Is [service] worth it for a company our size?
  • Source: sales call, stage: comparing options

What do Search Console and Bing tell you about AI questions?

Search Console cannot show you ChatGPT prompts, but it shows the typed searches that already reach you. Google says traffic from AI Overviews and AI Mode is included in the Performance report under the Web search type 2. Filter your queries for long, question-shaped phrases, using the regex in the templates below.

Google also rolled out a generative AI performance report to all websites worldwide as of 31 August 2026. It reports impressions only, by page, country, date and device 4. It will not show the questions, but it shows which of your pages the AI features already surface, which tells you where you are strong.

Bing goes further. Its AI Performance report, launched in public preview on 10 February 2026, lists grounding queries: the key phrases an AI used when retrieving content it later cited. Microsoft calls this a sample of overall citation activity 5. If you are cited at all in Copilot, this is the nearest thing to a view of the AI's own search terms.

How do AI follow-ups and forums add to the list?

Ask an assistant your core question and note the follow-up questions it suggests and the sub-topics it covers in the answer. Do this in two or three assistants and keep the overlap. The free Query Fan-Out Explorer shows the searches an AI runs for a prompt, which is a faster version of the same idea. See how to do query fan-out research for the full method.

Forums show unfiltered problems. Semrush studied 217,000 prompts across Google AI Mode, Perplexity and ChatGPT Search and found that Q&A threads made up more than half of the Reddit citations 6. Read threads in your field, copy the title questions and tag what the thread's top answer missed.

Be careful with vendor data. Semrush sells AI visibility tools, and its article does not explain how its prompts were chosen 6. Use studies like this to decide where to look, not as proof of what your buyers ask.

Where do question lists go wrong?

The first mistake is trusting one source. A keyword tool, a single AI answer or one sales call each shows a narrow slice. Require two sources before a question earns a page.

The second is collecting questions you cannot answer better than anyone else. Google warns that creating a separate page for every variation of a query, mainly to manipulate rankings or AI answers, breaks its scaled content abuse spam policy 7. Group near-identical questions onto one strong page.

The third is ignoring wording drift. AI answers are volatile, as Ahrefs notes, so its advice is to track a sample of prompts and see who gets recommended 8. Your list is a sample too, so refresh it.

Is your question list any good?

Test the list in two ways. First, run your top ten questions through two assistants and check whether the answers mention the topics you can cover. If the AI answers confidently and cites nobody like you, you have a gap to fill.

Second, show the list to a salesperson. If they say 'we hear that weekly' for at least seven of ten, your list matches the market. If they shrug, you are guessing.

Profound found that the choice of prompts shifted citation-share numbers more than running the same prompts more often 9. That supports spending your time on a good list rather than a huge one. Build the finished list into a monthly tracker using how to build a prompt list for tracking.

When is this not worth doing?

Skip the full process if you have no customers to learn from yet or a very narrow offer with a handful of obvious questions. In that case write down the ten questions you would ask as a buyer, answer them well, and revisit once you have real conversations.

Also skip it if your site blocks AI crawlers or hides its text behind scripts. Fix access first with the crawler check guide, because a perfect question list cannot help a page nobody can read.

Frequently asked questions

Is there a tool that shows exactly what people ask ChatGPT?

We found no tool that shows every real prompt. Vendors sell estimates built from sampled or modelled prompts. Bing's AI Performance report lists grounding queries, but Microsoft describes them as a sample 5. Use several sources and trust questions that appear in more than one.

Do ChatGPT questions match Google keywords?

Partly. Ahrefs found that ChatGPT's fan-out queries often include words such as 'official', 'price' and the year, which resemble search habits 3. But many ChatGPT answers involve no search at all, so keyword tools miss part of the picture.

How many questions should I collect?

Aim for 30 to 50 questions in a first list, then build pages for the ten that score highest. A longer list adds work without adding answers. Refresh the list monthly and drop questions that no longer appear in any source.

Can I just ask ChatGPT what its users ask?

You can, but the reply is a guess generated from patterns, not a log of real prompts. Use it to brainstorm, then confirm each idea against a call, a ticket, a Search Console row or a forum thread before writing a page.

Does the free Query Fan-Out Explorer replace this process?

No. It shows the searches an AI runs for one prompt you already have. This guide helps you find the prompts in the first place. Use the two together: gather questions here, then explore the fan-out for your top ten.

About the author

Rahil Jain

Rahil Jain is an AI SEO (answer engine and generative engine optimisation) consultant and co-founder of Chalk Labs.

LinkedIn · Method and credentials

Sources

  1. NBER Working Paper 34255: How People Use ChatGPT · National Bureau of Economic ResearchOpened October 20, 2026. Supports: The three most common conversation topics (Practical Guidance, Seeking Information, Writing) account for nearly 80% of conversations; sample size not stated on the abstract page.
  2. AI features and your website · Google Search CentralOpened October 20, 2026. Supports: AI Overviews and AI Mode may use query fan-out; AI feature traffic is reported in the Performance report under the Web search type; last updated 2025-12-10.
  3. How ChatGPT Does Query Fan-Out (15 Million Queries Studied) · AhrefsOpened October 20, 2026. Supports: 66.6 million logged-out ChatGPT responses, 14.4% triggered a search with about 1.6 fan-out queries each; 'price' rose from 6.0% to 8.9%; 'official' in 13.1% of English fan-outs; 84.4% vs 68.3% official-source citation split.
  4. Generative AI performance report · Google Search Console HelpOpened October 20, 2026. Supports: Report covers AI Overviews and AI Mode, impressions only, by page, country, date and device; rolled out to all websites as of 31 August 2026.
  5. Introducing AI Performance in Bing Webmaster Tools Public Preview · Microsoft Bing Webmaster BlogOpened October 20, 2026. Supports: Announced 10 February 2026; grounding queries are key phrases the AI used when retrieving content it cited, and are a sample of overall citation activity.
  6. Reddit AI Search Visibility Study · SemrushOpened October 20, 2026. Supports: 217,000 prompts across AI Mode, Perplexity and ChatGPT Search; Q&A threads over half of Reddit citations; prompt selection not explained; vendor sells AI visibility tools.
  7. Optimizing your website for generative AI features on Google Search · Google Search CentralOpened October 20, 2026. Supports: Separate pages for every query variation made primarily to manipulate rankings or AI responses violate the scaled content abuse policy; last updated 2026-07-10.
  8. How to Measure AI Search Visibility When Attribution Falls Short · AhrefsOpened October 20, 2026. Supports: Advice to track a sample of prompts and see who gets recommended; AI answers are inherently volatile; dated 6 October 2026.
  9. Is once a day enough? · ProfoundOpened October 20, 2026. Supports: Prompt portfolio composition mattered more than run frequency for citation share; internal 14-day test of 753 prompts; vendor sells tracking.
How this page was made. Built on Rahil Jain's AI SEO method and drafted with AI research assistance. Every statistic links to the page we read it on (opened October 20, 2026 or nearby). Published October 20, 2026; last updated October 20, 2026. Chalk Labs sells AI SEO services, so we have a commercial interest in this topic. Spotted an error? Tell us and we will fix it.