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| Criterion |  Growth A/B Testing |  Decision Making Three-Point Estimation |  Agile NoEstimates |  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. | 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 estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules. | 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 | Medium | Medium | Medium |
Timedifferent | 1-4 Wochen | 10-30 min je Item | laufend | 1-5 Tage |
Participantsdifferent | 1-6 | 1-8 | 2-12 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Three-Point Estimate, Risk Range, Assumption Notes | Throughput Data, Flow Forecast, Slicing Rules | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | EstimationUncertaintyForecasting | EstimationForecastingFlow | ValidationExperimentsDemandDiscovery |