Real buyer questions per industry, grouped by intent — the starting point for a prompt set that measures discovery rather than your own brand name.
For B2B SaaS, AI visibility is decided in the shortlist phase: a buyer asks an assistant which tools solve a problem, and two or three names come back. Tracking that means running the questions buyers actually ask — category best-of, head-to-head comparisons, integration questions, pricing questions and switching questions — rather than your own brand name.
In e-commerce the AI answer often replaces the category page: a shopper asks for the best product for a situation and receives three recommendations with links. Visibility here is product- and use-case-shaped rather than brand-shaped, so the prompt set has to follow how shoppers describe problems, constraints and budgets.
For local service businesses, AI answers behave like a referral: the assistant names two or three providers for a place and a job. What decides inclusion is rarely brand strength — it is whether the service, the area served and the practical details are stated plainly somewhere an engine can retrieve and attribute.
Agencies are chosen through questions that mix capability, price and trust, and AI assistants answer them by describing categories of agency rather than naming many brands. Tracking that means measuring both whether you are named and whether the description of your specialism matches what you actually sell.
Fintech answers are constrained by caution: assistants hedge on money questions, prefer regulated and well-documented sources, and often describe categories instead of naming providers. Visibility work here is about being the clearly documented, verifiable option rather than the loudest one.
