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| Criterion |  Growth Funnel Analysis |  Growth North Star Metric |  Growth Growth Experiment |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible. | When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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. |
Complexitydifferent | Medium | Medium | Medium | High |
Timedifferent | 1-3 h | 1-2 h | 1-2 Wochen | 1-4 Wochen |
Participantsdifferent | 1-5 | 3-8 | 1-6 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | North Star metric, Input metric tree, Measurement cadence | Experiment card, Result summary, Next bet | Experiment results, Decision log, Learning summary |
Tags1 shared | AnalyticsConversionGrowth | GrowthMetricsAlignmentRetention | MarketingGrowthExperimentsLearning | ExperimentsGrowthAnalyticsValidation |