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| Criterion |  Growth A/B Testing |  Facilitation Dot Estimation |  Product Discovery Smoke Test |  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 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 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 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 | 5-20 min | 1-5 Tage | 1-3 h |
Participantsdifferent | 1-6 | 3-20 | Nutzertraffic | 1-5 |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Effort Heatmap, Risk Signals, Discussion Targets | Interest Metrics, Conversion Signal, Learning Note | Funnel report, Drop-off analysis, Optimization hypotheses |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | EstimationEffortRisk | ValidationExperimentsDemandGrowth | AnalyticsConversionGrowth |