Prompt research
In short
Research into the questions and instructions people use, or are likely to use, when exploring a topic through AI systems.
Prompt research identifies questions worth investigating in AI search and assistants. For a merchant, these might concern product suitability, comparisons, compatibility, delivery, or alternatives.
Useful inputs include customer questions, site-search records, support conversations, and a research tool’s documented query data. Keep observed customer language separate from prompts generated as hypotheses.
A practical example
Imagine shoppers repeatedly asking whether a stroller fits a small car trunk. The retailer creates a research group around folded dimensions, wheel removal, and comparison with similar models.
It can then test a few representative prompts and inspect the answers. This illustrative example connects a purchase decision with content needs. It does not establish how many people ask any exact phrase in an AI service.
Research intent, not endless variations
Hundreds of rewordings can cover the same decision while missing another important concern. Group questions by what the buyer needs to resolve, then choose a manageable set for monitoring.
Treat reported prompt volumes and audience estimates according to the provider’s methodology. A vendor database is not a complete log of private conversations. Record where each research idea came from, which market it covers, and whether it represents observed behavior or a question you still need to validate.