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| Criterion |  Decision Making Decision Tree |  Product Discovery Fake Door Test |  Decision Making Constraint Analysis |  Product Discovery Riskiest Assumption 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 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. | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | When an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 30-90 min | 1-5 Tage | 30-90 min | 1-2 Wochen pro Iteration |
Participantsdifferent | 1-6 | Nutzertraffic | 2-8 | 2-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Click Data, Interest Signal, Learning Decision | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Prioritized Assumption List, Test Plan, Results Report |
Tagsno overlap | DecisionTreeOptions | ValidationExperimentsDemandDiscovery | ConstraintsDecisionPlanningOptions | ExperimentsValidationDiscoveryAssumptions |