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| Criterion |  Decision Making Decision Tree |  Product Discovery Pretotyping |  Decision Making Constraint Analysis |  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. | Pretotyping clarifies whether a customer problem and solution idea create enough real demand. It separates problem, assumption, solution, and evidence, and captures the result as a pretotyping sketch, test setup, and conversion data. | 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 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. |
Complexitydifferent | Medium | Low | Low | Medium |
Timedifferent | 30-90 min | Stunden bis wenige Tage | 30-90 min | 1-5 Tage |
Participantsdifferent | 1-6 | 1-4 | 2-8 | Nutzertraffic |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Pretotyping sketch, Test setup, Conversion data, Go or no-go decision | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | DecisionTreeOptions | ValidationDemandMVP | ConstraintsDecisionPlanningOptions | ValidationExperimentsDemandDiscovery |