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| Criterion |  Growth A/B Testing |  Decision Making PERT Estimation |  Product Discovery Hypothesis Prioritization Canvas |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
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. | On complex initiatives, a plain average tends to understate just how uncertain the outcome really is. It separates options, evaluation criteria, and open risks. The result is captured as a PERT Estimate, Expected Value, and Risk Notes. | When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | High | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 15-45 min | 60-90 min | 45-60 min |
Participantsdifferent | 1-6 | 1-8 | 3-8 | 2-8 |
Formatdifferent | Async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | PERT Estimate, Expected Value, Risk Notes | Prioritization Canvas, Hypothesis Backlog | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | EstimationUncertaintyRisk | ExperimentsPrioritizationDiscoveryHypothesis | AssumptionsRiskExperimentsValidation |