Product discovery

Product discovery

Discovery de-risks building. The question is never "is this idea good" but "what evidence shows this problem is real, frequent, and painful enough that someone changes behavior to solve it".

Method

1. Start from the problem space, held open. Write the target outcome (business and user), then map opportunities beneath it (an opportunity solution tree: outcome, opportunities, candidate solutions, experiments). Solutions arriving first get parked as candidates under whichever opportunity they claim to serve; if none fits, that is the finding.
2. Grade evidence by what it cost the user. Weakest to strongest: opinions in a meeting, survey answers, interview stories about the past (see customer-interviews), observed current behavior and workarounds, and paid/effortful commitment (signed up, prepaid, switched tools). Fund decisions on the top half; a deck of survey percentages is not discovery.
3. Hunt the workaround. Users solving the problem today with spreadsheets, interns, or duct tape prove frequency and pain at once: the workaround is the demand signal and the competing product. No workaround usually means no felt problem, whatever the interviews politely said.
4. Size before you commit. How many users hit this, how often, at what cost each time (see estimation-techniques for honest Fermi work); a real problem afflicting few people rarely is a segment decision, not a roadmap item. Check the result against the outcome it claims to move (see product-metrics).
5. Run the cheapest killing experiment. For the riskiest assumption, choose the test that could disprove it fastest: landing-page demand tests, concierge/manual service, fake door (ethically: tell users after; see mvp-scoping), prototype walkthroughs. Write the pass/fail bar before running (see hypothesis-driven-work); experiments without kill criteria are theater.
6. Close the loop visibly. Each discovery cycle ends in a decision (pursue, park, kill) recorded with its evidence (see decision-journals, architecture-decision-records' sibling for product); killed ideas with reasons prevent their monthly resurrection.

Boundaries

• Discovery is continuous, not a phase gate; a quarter of pure research with no shipped learning is its own failure mode (see mvp-scoping's ship-to-learn).
• Some bets are vision-driven and evidence-light by nature; label them as such deliberately rather than laundering them through fake validation.
• B2B discovery must separate buyer, user, and blocker personas; one enthusiastic champion is not a validated market (see customer-interviews' recruiting).