Which prompts to track? Building a representative monitoring set

You should track the prompts your buyers actually ask AI, not the keywords with the highest volume. A useful monitoring set is a deliberate selection of buying questions, spread across funnel stages, industries and regions, so you can measure whether AI mentions your brand at the moments that lead to revenue. This article shows how to build such a representative prompt set, how large it should be and how to maintain it.

This fits within the broader framework of our guide to Generative Engine Optimization. Where GEO determines how you become visible in AI answers, your prompt set determines whether you can measure that visibility reliably.

What is a prompt set and why does it matter?

A prompt set is the fixed list of questions you periodically put to AI systems to measure whether, how and in what context your brand is mentioned. It is the AI equivalent of a keyword list in classic SEO, with one important difference: a prompt is a full question in natural language, not a single term. In ChatGPT or Perplexity, people don’t type “fleet management software”, but “what is the best fleet management software for a transport company in Belgium”.

That set matters because it determines what you can see at all. If you measure the wrong questions, you get a reassuring or alarming report that has nothing to do with your real commercial position. A brand can score brilliantly on broad informational questions while being completely invisible the moment a buyer asks for a concrete recommendation. The prompt set is therefore not an administrative detail, but the yardstick itself.

Which prompts should you track?

Track the prompts in which a buyer makes a choice, compares or asks for a recommendation, because that is where your visibility turns into a lead. Don’t start with search volume, but with the questions your sales team hears every day. Four types of prompts belong in every serious set:

• Category questions. “Best [category] for [type of company]” or “which [solution] should I choose for [situation]”. These are the recommendation moments where you want to be mentioned.
• Comparison questions. “[Brand A] vs [Brand B]” or “alternatives to [known player]”. Here AI decides whether you are in the consideration set.
• Problem questions. “How do I solve [problem]”. Here AI can put your approach or brand forward as a solution direction.
• Brand questions. “What does [your brand] do” or “is [your brand] reliable”. Here you check whether AI describes you correctly and consistently.

The biggest mistake is filling the set with general informational questions because they seem to have the most “volume”. A question like “what is email marketing” produces a neat answer, but rarely a brand name and never a lead. At Customer Impact we steer clients away from those vanity metrics: we measure visibility on the questions buyers ask right before they get in touch, not on the questions that look busy in a report.

How do you distribute prompts across the funnel?

A representative set deliberately spreads your prompts across the three funnel stages, so you can see where your visibility drops off. Many brands are perfectly visible at the top of the funnel and disappear precisely where the decision is made. By measuring per stage, you make that gap visible instead of averaging it into a vague overall figure.

• TOFU (awareness). Broad problem and how-to questions. Here you want to be mentioned or cited as a source, not necessarily as a product. A handful of prompts is enough, because this is rarely where you win or lose.
• MOFU (consideration). Category and comparison questions. This is the core of your set and deserves the most prompts, because here AI decides whether you make the shortlist.
• BOFU (decision). Concrete buying, pricing and provider questions, often with a region or industry in them. “Who can deliver [service] in [region]”. Here every mention counts directly.

For B2B the centre of gravity deliberately lies with MOFU and BOFU, because that is where the buying decisions are made. How to fill those stages in further, you can read in our take on GEO for B2B. A healthy distribution is roughly a quarter of your prompts in TOFU, half in MOFU and a quarter in BOFU, but adjust that to your own buying journey.

How do you account for industry and region?

Explicitly add industry, company type and region to your prompts, because AI answers vary strongly by context and a generic question hides where you are really strong or weak. “Best accounting software” gives a different answer than “best accounting software for a sole trader in Flanders”. If your customers mainly come from a specific sector or region, your set has to carry that context.

So work with variants of the same core question in which you swap out one dimension each time: the industry, the company size, the language or the region. That way you see not only whether you are mentioned, but also where your position falls away. A brand that scores well in Dutch may be unfindable in a French-language variant of the same question, which in Belgium is a real risk. This touches on how AI determines who is relevant for which context, the subject of our five key indicators of AI visibility.

How large should your prompt set be?

Keep your set as small as responsible and as large as necessary: better thirty to sixty sharp prompts that you follow consistently than hundreds of variants that no one still interprets. The point of monitoring is to steer, and you can only steer on a set that you genuinely understand and check regularly.

A workable approach is to build a small cluster per core theme: a category question, one or two comparison variants and an industry or region variant. If you have five to ten commercially relevant themes, you naturally land on a set that is complete enough without becoming unmanageable. More important than the size is consistency: the same prompts, at fixed moments, so that shifts gain meaning. Asking a hundred questions once is a snapshot, not monitoring.

Also mind the practical side. AI answers vary between models and even between repeated questions, so you want to measure each prompt on multiple systems and with some repetition. The more prompts, the heavier that weighs. A compact, well-chosen set is therefore not only clearer, but also more affordable to run consistently. Which platforms and measurement methods fit here, we compare in our overview of AI visibility tools.

How do you maintain your prompt set?

Treat your prompt set as a living document that you revise every quarter, because buying behaviour and the way people query AI change faster than classic search habits. A set you leave unchanged for a year slowly measures the wrong reality.

Three sources feed that revision. First your sales team: new objections and questions from prospects are often new prompts. Second the AI answers themselves, because the follow-up questions and related topics that models suggest show how buyers think further. Third your competitors: if a new player appears in the comparison answers, it belongs in your comparison prompts. Just as readily, remove prompts that no longer give a usable signal. A sharp set stays sharp through pruning, not only through adding.

If you want to measure this without having to learn to understand the models yourself, our service for AI visibility helps you set up a representative set and translate the signals into concrete actions.

The short summary

A good prompt set measures your real commercial position in AI answers, not your scoring chances on broad informational questions. Start from the questions buyers ask, deliberately spread them across funnel stages, industries and regions, keep the set compact and revise it every quarter. That way AI visibility becomes a steerable number instead of a reassuring report.

Schedule your free intake and we’ll build a prompt set together that measures what matters for your business.