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| Criterion |  Decision Making Decision Tree |  Product Discovery Problem Interview |  Product Discovery MVP Test Matrix |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. | 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 | 30-90 min | 30-60 min je Interview | 45-75 min | 1-5 Tage |
Participantsdifferent | 1-6 | 5-12 Interviews | 2-8 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Problem Evidence, Risk Notes, Customer Segments | Test Matrix, Test Plan | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | DecisionTreeOptions | DiscoveryInterviewsValidation | ExperimentsValidationDiscoveryOptions | ValidationExperimentsDemandDiscovery |