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| Criterion |  Growth A/B Testing |  Product Discovery Smoke Test |  Facilitation Dot Estimation |  Growth Funnel Analysis |
|---|---|---|---|---|
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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | When size or effort can only be estimated roughly, Dot Estimation condenses the group's experience into a quick range. It turns individual contributions into a visible selection. The result is captured as an Effort Heatmap, Risk Signals, and Discussion Targets. | 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. |
Complexitydifferent | High | Low | Low | Medium |
Timedifferent | 1-4 Wochen | 1-5 Tage | 5-20 min | 1-3 h |
Participantsdifferent | 1-6 | Nutzertraffic | 3-20 | 1-5 |
Formatdifferent | Async | Async | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note | Effort Heatmap, Risk Signals, Discussion Targets | Funnel report, Drop-off analysis, Optimization hypotheses |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth | EstimationEffortRisk | AnalyticsConversionGrowth |