A new product question does not always require starting with an empty notebook. Earlier interviews, support conversations, open survey answers, and study reports may already contain relevant evidence. Insight mining is the work of finding and analysing that material for the question now at hand.

The term describes a practice rather than a single standardised method. Its quality depends on which material is included, how it is searched, and whether the original circumstances remain attached to the conclusions.

Define the question before searching

“Find interesting feedback” can produce a persuasive collection of comments with no clear decision behind it. “What do we already know about why administrators delay inviting colleagues?” gives the search a useful boundary.

Identify relevant sources and dates, then search beyond one keyword. People may describe inviting colleagues as adding users, sharing access, setting up a team, or asking someone to join. Search terms should develop as the material reveals how people express the experience.

Ballpark’s Coach documentation describes assistance with analysing existing study material. Automated retrieval can help locate passages, but inspect the source and scope of each answer rather than assuming every relevant record was available to the system.

Reconstruct the circumstances around each account

An incidental comment about price in an onboarding interview has a different context from an answer to a direct pricing question. A support ticket represents someone who contacted support, while silent customers may have experienced the same difficulty differently or not at all.

In an illustrative review, several mentions of delayed invitations might come from one organisation with a strict approval policy. Keep that relationship visible. Counting mentions without examining their origin could turn a local constraint into an apparently widespread need.

Use thematic analysis or another appropriate approach when the task requires interpretation across material. Retrieval finds candidate evidence; analysis examines what it means, where accounts agree, and where they do not.

Decide whether the existing evidence is enough

Sometimes the archive answers a narrow question adequately. Sometimes it provides a useful starting point but lacks the right audience, product version, or detail. State that gap specifically so new research can address it.

A good output distinguishes supported findings, plausible interpretations, and unanswered questions. Link back to the original studies and explain the search coverage, including important sources that were unavailable. This also strengthens knowledge management, because the next researcher can build on the review instead of repeating the same search without knowing what was already considered.