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| Criterion |  Knowledge Modeling Event Modeling |  Product Discovery Problem Interview |  Product Discovery Concierge MVP |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | Event Modeling connects business workflows with commands, events, and views into one coherent mental model. It helps design behavior, UI, and technical slices from the same underlying logic. | 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 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 | 2-6 h | 30-60 min je Interview | 1-4 Wochen | 30-60 min |
Participantsdifferent | 2-8 | 5-12 Interviews | 3-10 Kunden | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Event Model, UI Flow, Commands, Read Models | Problem Evidence, Risk Notes, Customer Segments | Concierge Learnings, Service Blueprint, MVP Risks | Completed Experiment Canvas, Success Metric |
Tagsno overlap | EventsBlueprintDomain-Driven DesignBehavior | DiscoveryInterviewsValidation | MVPValidationServiceDiscovery | ExperimentsValidationDiscoveryHypothesis |