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| Criterion |  Growth A/B Testing |  Decision Making Three-Point Estimation |  Growth Funnel Analysis |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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. | A single estimate for effort, time, or risk often looks too smooth for the real uncertainty behind it. It separates options, evaluation criteria, and open risks. The result is captured as a Three-Point Estimate, Risk Range, and Assumption Notes. | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 10-30 min je Item | 1-3 h | 30-60 min |
Participantsdifferent | 1-6 | 1-8 | 1-5 | 1-5 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Three-Point Estimate, Risk Range, Assumption Notes | Funnel report, Drop-off analysis, Optimization hypotheses | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | EstimationUncertaintyForecasting | AnalyticsConversionGrowth | ExperimentsValidationDiscoveryHypothesis |