Prompts and topics

A prompt is a question you want to investigate in AI search. Topics organize related questions; the prompt’s cohort preserves what kind of question it is.

Start with a decision, not a keyword list

Write questions a buyer could ask while understanding a problem, comparing approaches or choosing a product. Be specific about the audience and constraint when they matter.

For a fictional analytics company:

• “What should a small ecommerce team use to understand repeat purchases?”
• “Which analytics tools support a team without a data engineer?”
• “How does Example Analytics compare with another named product?”

The comparison prompt names a brand. Keep that framing separate from discovery questions where the answer has to introduce brands itself.

Review generated suggestions

Generated prompts use your project context. If the context is wrong, fix it before growing the portfolio. Check for irrelevant markets, unsupported product claims and repetitive questions.

A suggestion is not permission to activate or run it. Use the review and activation controls provided in the app, then select the portfolio you want to measure.

Keep a stable baseline

A small, coherent portfolio is easier to interpret than a large collection of loosely related questions. Once you have a baseline, record deliberate changes to prompt wording, cohorts or engine selection.

Historical audits keep the prompt text and measurement context used at the time. Editing a prompt later does not rewrite an earlier answer.

Read individual answers

When an aggregate looks surprising, open the underlying execution in Runs. Check the actual wording, brand observation and citation evidence before rewriting your strategy.

Missing, failed and not-run answers are different from successful answers that did not mention the brand.

What to do next

Run an audit and use AI Visibility to inspect results. For product-specific buying questions and AI Shelf, use Commerce.