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| Criterion |  Product Discovery Problem Interview |  Product Discovery Concierge MVP |  Domain Modeling EventStorming |  Product Discovery Experiment 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 an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | 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. |
Complexitydifferent | Medium | Medium | Medium | Low |
Timedifferent | 30-60 min je Interview | 1-4 Wochen | 2-8 h | 30-60 min |
Participantsdifferent | 5-12 Interviews | 3-10 Kunden | 5-12 | 1-5 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Problem Evidence, Risk Notes, Customer Segments | Concierge Learnings, Service Blueprint, MVP Risks | Event Timeline, Ubiquitous Language, Boundaries, Open Questions | Completed Experiment Canvas, Success Metric |
Tags1 shared | DiscoveryInterviewsValidation | MVPValidationServiceDiscovery | Domain-Driven DesignEventsDiscoveryWorkshop | ExperimentsValidationDiscoveryHypothesis |