Collect the language customers use
Start with sales notes, support questions and the phrases customers use when explaining their problem. Include questions about categories, alternatives, use cases and constraints. Avoid beginning with a list of keywords copied into question form. A useful question set represents decisions people make. Keep a record of where each question came from so you can explain its inclusion and replace weak assumptions when better customer evidence becomes available. The first version can be small and still be useful.
Separate discovery from brand questions
An unbranded question asks which products or services could solve a problem. A branded question asks about a company already under consideration. Both can be useful, but they describe different stages of a decision. Group them separately and label them clearly in reports. A brand appearing in answers that explicitly name it tells you something different from appearing in broad category discovery. Combining them into one unexplained percentage makes the result harder to interpret.
Cover the important buying situations
Include the use cases and constraints that influence your buyers: team size, geography, required features or an existing workflow. Choose a manageable number of variations rather than every possible sentence. Give each question a purpose and an owner. If two questions support the same decision, consider whether both are necessary. A focused set is easier to inspect and maintain. You can expand it once the first reports reveal a genuine gap in what your team needs to understand.
Six kinds of question worth tracking
Keep a stable reporting group
Create one group of questions that stays consistent across reporting periods. Use another group for experiments and new ideas. Record wording changes and avoid comparing a revised set with an older set as if nothing changed. A change in the sample can move a headline number even if the underlying answers are similar. Keeping the stable group intact helps you distinguish a measurement change from a change in what AI products say about your brand.
Read the actual answers
Inspect an initial sample before committing to recurring collection. Remove questions that produce irrelevant answers or cannot reasonably connect to your business. Look for ambiguous wording and accidental references to a brand with the same name. Keep difficult questions when they represent a real customer concern, even if the result is unflattering. The purpose is to learn about the decision environment, not build a set designed to produce a reassuring dashboard for the next meeting.
Review the set with a reason
Schedule a review when your product, market or customer questions change. Preserve a history of additions and removals. Ask which results led to a decision and which were repeatedly ignored. Retire questions that no longer represent a useful buying situation, but explain the effect on comparisons over time. Your set should evolve deliberately. More questions can add cost and reporting work without adding understanding, so expand around identified needs rather than a provider’s available allowance.