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| Criterion |  Product Discovery Problem Interview |  Domain Modeling EventStorming |  Product Discovery Experiment Canvas |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | When the picture of the problem still needs to become solid, it asks about real situations and consequences. It separates genuine suffering from mere interest in a solution. | When a domain consists of many events, rules, and states, it creates a shared modeling space for the team. It bundles language, flows, and boundaries before domain knowledge fragments into siloed views. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 30-60 min je Interview | 2-8 h | 30-60 min | 60-90 min |
Participantsdifferent | 5-12 Interviews | 5-12 | 1-5 | 3-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Problem Evidence, Risk Notes, Customer Segments | Event Timeline, Ubiquitous Language, Boundaries, Open Questions | Completed Experiment Canvas, Success Metric | Prioritization Canvas, Hypothesis Backlog |
Tags1 shared | DiscoveryInterviewsValidation | Domain-Driven DesignEventsDiscoveryWorkshop | ExperimentsValidationDiscoveryHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |