How To Find The Questions Buyers Ask AI Search Engines

A three-person bookkeeping and payroll firm posted in r/CRMSoftware this month. They had 2,800 contacts in spreadsheets, wanted a CRM that could also send a monthly newsletter, and kept finding tools that were either thin on email or expensive per contact. Their question was long and specific, about a firm their size with their exact needs.

That's what a buyer question looks like when someone asks an AI. Google autocomplete for the same market shows "crm for small business free." Both describe the same buyer, at very different resolutions. To find the questions buyers actually ask AI search engines, you need sources that show both.

So we tested four of them side by side.

What we compared

On October 19, 2026, we picked three markets, small-business CRM software, running shoes and small-business accountants. For each, we pulled questions from four sources through a data provider's live US feed and Reddit's search.

1. Google autocomplete, for the seed term and variants like "best," "vs," "for" and "how much."
2. Google's People Also Ask boxes, for the seed term and its "best" version.
3. Reddit post titles from the past year.
4. The web searches ChatGPT ran when we asked it 11 buyer questions, three or four per market. These are called fan-out queries.

Then we sorted every result by whether it was a decision-stage question, about comparing, pricing or choosing, and whether it named a brand or the year.

Each source found something the others missed. None of them, alone, gives you a list of questions to track.

Your competitors are getting cited by AI. You're not.

Every day without citation tracking is a day your competitors pull ahead in ChatGPT, Perplexity, and Claude.

Show me who's getting cited →2-minute overview · real case-study numbers

Autocomplete shows who's asking

Autocomplete was the biggest source by far, and almost none of it was a full question. What it shows is segments. For CRM software, the suggestions split by country ("uk," "india," "australia"), by industry ("construction") and by budget ("free," "open source," "cheap"). For accountants, they split by city and by need ("taxes," "llc," "start up").

That's useful. Each segment is a different buyer who'll ask a different question. "Best CRM for a construction company with 10 field staff" and "free CRM for a one-person agency" get different answers, and you want to know which ones you show up for.

Use autocomplete to list your buyer segments, then write the full question each segment would ask.

People Also Ask shows objections, with noise

Every People Also Ask result was a real question, which makes it look like the perfect source. It's patchier than it looks. Google showed none at all for "running shoes." For accountants, the questions drifted from hiring one to learning bookkeeping, like "what are the three golden rules of bookkeeping?"

The good ones are objections and definitions a buyer has before choosing. "Is CRM difficult to learn?" and "what are the disadvantages of CRM?" are exactly what someone wonders before they buy. Keep those, and drop the ones that wander off your buyer's path.

Reddit shows the real phrasing

Reddit titles were the closest to how people talk. "Which CRM did your team actually keep using, and what made you drop the others?" "What are the best running shoes that you'd actually buy again?" "How do small businesses find a good accountant or bookkeeper?"

These carry the detail AI questions have, like team size, a past mistake or a budget. They also show the criteria buyers care about, like whether a team keeps using the tool after the first month. Those criteria belong in your questions and in your content.

ChatGPT's own searches show the shortlist

The smallest source was the most revealing. When we asked ChatGPT our buyer questions, it ran 10 web searches across the three markets. Nine were decision-stage, all 10 added the year, and 7 named brands.

One CRM search named HubSpot, Zoho, Pipedrive, Salesforce and Freshsales, plus "pricing features." Two more asked for HubSpot's and Salesforce's official pricing pages. For running shoes for beginners, it searched for the Brooks Ghost, Hoka Clifton and ASICS models by name. For accountants, it searched for how to verify a CPA's license.

That tells you two things. First, which brands ChatGPT already has on its shortlist before it reads a single page. Second, what it looks for to decide, which in these markets was pricing, comparisons and reviews from the current year. Our guide to how ChatGPT searches the web covers this rewriting step in more depth.

RANKCONTROL

200+ SaaS teams already track their AI citations.

They know exactly when ChatGPT mentions their brand, and when it stops. Do you?

Show me the plan →One plan · everything included

Turn the four sources into a question set

Here's how we'd combine them into a set of questions to track.

1. List your buyer segments from autocomplete, like company size, industry, location and budget.
2. For each segment, write two or three full questions in a buyer's voice, using phrasing from Reddit, your sales calls and support tickets.
3. Add the objections from People Also Ask that sit on your buyer's path.
4. Ask ChatGPT a few of the questions and note what it searches for. Add the decision words it uses, like pricing or comparison, to your questions.
5. Mix the set across comparison, pricing and "best X for Y" questions, with a few problem questions from earlier in the journey.
6. Keep 20 to 50 core questions fixed, so changes from week to week mean something.

Your own data beats all four public sources. Sales call notes, support tickets and the long questions now showing up in Google Search Console are your buyers' own words. Our guide to using AI-style queries from Search Console covers that last source.

A worked example for CRM software

Here's what that process produced for the small-business CRM market, using only what the four sources showed us.

Notice what none of the sources gave us directly. The bookkeeping firm's real question combined a CRM, a monthly newsletter, 2,800 contacts and a three-person team. No autocomplete list or People Also Ask box carries that much detail. That kind of question comes from your own sales calls and support tickets, which is why they belong in the set.

Then test the questions in the engines

A question list is a guess until you ask it. Run each question in ChatGPT, Perplexity, Google AI Mode and the other engines your buyers use, and note who gets named, which sources get cited, and whether you appear.

Our earlier guide to finding buyer questions AI assistants actually answer covers filtering the list down to the ones worth chasing. And if you're planning content from them, our post on using AI search queries to plan content turns the searches into a calendar.

Limits of our test

We tested three markets, on one day, from a US feed. ChatGPT searched for only some of our questions, so the fan-out sample is small at 10 searches. Reddit titles came from one search per market. We sorted questions with simple word rules, so a few may be in the wrong group.

What this takes by hand

Here's a rough budget for building and maintaining a question set, by our estimate.

Doing it by hand or with help

You can build and check the set yourself. Or RankControl can take on the steady part every month while you focus on your product. It finds the questions your buyers ask, and its AI visibility tracking checks 50 of them every week on ChatGPT, Perplexity, Claude, Gemini, Grok, Google AI Mode and Google AI Overviews, showing who gets named and which sources each engine cites.

RANKCONTROL

How often does ChatGPT mention your brand?

Most founders have no idea. The answer might surprise you.

Show me my mentions →50 queries tracked · all 7 AI models