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| Criterion |  Growth A/B Testing |  Decision Making Constraint Analysis |  Product Discovery MVP Test Matrix |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. | 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 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. |
Complexitydifferent | High | Low | Medium | Medium |
Timedifferent | 1-4 Wochen | 30-90 min | 45-75 min | 1-5 Tage |
Participantsdifferent | 1-6 | 2-8 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Test Matrix, Test Plan | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ConstraintsDecisionPlanningOptions | ExperimentsValidationDiscoveryOptions | ValidationExperimentsDemandDiscovery |