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| Criterion |  Growth North Star Metric |  Growth Growth Experiment |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 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 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 | Low | High |
Timedifferent | 1-2 h | 1-2 Wochen | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-8 | 1-6 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | North Star metric, Input metric tree, Measurement cadence | Experiment card, Result summary, Next bet | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tags1 shared | GrowthMetricsAlignmentRetention | MarketingGrowthExperimentsLearning | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |