How to Find the Prompts Your Buyers Actually Ask AI

Every AI visibility program stands on one decision: which prompts you track. Track the questions buyers genuinely ask an assistant and your measurements describe reality. Track vanity phrasings and you optimize a mirage. Building the prompt set deserves the same rigor keyword research once got, with one twist: prompts are conversations, longer and more contextual than keywords ever were.

The good news is that buyer prompts follow patterns. You can construct a representative set in an afternoon from sources you already have.

Prompts are not keywords

Keyword research optimized for two or three word fragments because that is how people typed into a search box. People talk to assistants differently:

• They describe their situation. "We're a 40-person agency using spreadsheets for client reporting, what should we switch to?"
• They ask for judgments. "Best," "worth it," "should I," "which one" appear constantly.
• They iterate. A first question spawns follow-ups about pricing, integrations, and objections inside one session.
• They fan out. Engines decompose one prompt into several searches, so a single tracked prompt exercises a cluster of underlying queries.

The unit worth tracking is the question as a buyer would phrase it, verbatim and specific.

The five prompt archetypes

Nearly every commercial prompt set decomposes into five shapes. Build coverage across all of them:

1. Category discovery. "Best [category] tools for [context]." The listicle question where inclusion is the whole game.
2. Direct comparison. "[You] vs [competitor]" and "[competitor] alternatives." High intent, and the place where a wrong or missing answer costs the most.
3. Problem-first. "How do we stop [pain]" with no category named. The buyer does not know the category exists; the engine's framing decides which category, and whose brand, gets introduced.
4. Validation. "Is [your brand] good for [use case]," "is [brand] worth it." Answers here reflect your reputation footprint, reviews, and community sentiment.
5. Task-level. "How to [job your product does]." You want the answer to mention your approach or cite your resources.

Where to mine the actual language

Pull the phrasings from places buyers already wrote them down:

• Sales calls and demo requests. The questions prospects ask in the first ten minutes are the questions they asked an assistant the night before.
• Support and community threads. Real vocabulary, including the wrong vocabulary, which matters because engines answer the question as asked.
• People Also Ask and autocomplete. Still useful as a phrasing source even when the destination is an AI answer.
• Your competitors' comparison pages. They list the matchups buyers force them to answer.
• The engines themselves. Ask ChatGPT or Perplexity "what would someone ask before buying [category]" and mine the output for candidate phrasings to verify against real sources.

Write prompts exactly as a person would, typos of thought included. "whats the best crm that works with gmail for a small nonprofit" beats "best CRM Gmail nonprofit."

Sizing and structuring the set

More prompts is not automatically better. Every tracked prompt costs measurement runs, and a bloated set buries signal in noise:

• Start with 15 to 50 prompts weighted toward comparison and category-discovery shapes, where money changes hands.
• Group prompts by theme: pricing, alternatives, use cases, personas. Groups let you read visibility by intent instead of one prompt at a time, and they map directly to how prompt organization works in Citlyze.
• Localize where you sell. The same question phrased for different markets returns different brands. Track per market if regional presence matters.
• Version, don't churn. Trend lines require stable prompts. Add new ones freely; rewrite existing ones rarely and deliberately, because every rewrite resets that prompt's history.

Validate before you commit

Run each candidate prompt a few times across your target engines and check two things. First, that the answer type matches intent: if "best reporting tools" returns consumer apps and you sell enterprise software, sharpen the context. Second, that variance looks sane: answers naturally differ between runs, which is precisely why single checks mislead and why repeated sampling is the core of honest measurement, as we explain in why AI answers change.

FAQ

How many prompts should I track? Enough to cover the five archetypes for each product line and market, few enough to act on. Most teams do well between 15 and 100.

Should I track branded prompts? Yes, a handful. Validation prompts reveal how engines describe you, which catches accuracy and sentiment problems that category prompts never surface.

How often should the set change? Review quarterly. Add prompts for new products, competitors, and observed buyer language. Keep the core stable so trends stay comparable.

From prompt list to visibility dashboard

Citlyze turns your prompt set into scheduled measurements across ChatGPT, Gemini, Perplexity, DeepSeek, Grok, and Google's AI surfaces, with mention rates, cited sources, and competitor share per prompt group. See prompt tracking, or start a workspace and load your first prompts in minutes.