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| Criterion |  Product Discovery Concierge MVP |  Knowledge Modeling Event Modeling |  Product Discovery Problem Interview |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | 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. | 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 demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 2-6 h | 30-60 min je Interview | 1-5 Tage |
Participantsdifferent | 3-10 Kunden | 2-8 | 5-12 Interviews | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Concierge Learnings, Service Blueprint, MVP Risks | Event Model, UI Flow, Commands, Read Models | Problem Evidence, Risk Notes, Customer Segments | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | MVPValidationServiceDiscovery | EventsBlueprintDomain-Driven DesignBehavior | DiscoveryInterviewsValidation | ValidationExperimentsDemandDiscovery |