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| Criterion |  Growth North Star Metric |  Product Discovery Fake Door Test |  Growth Flywheel |  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 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. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. | 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 | 1-2 h | 1-5 Tage | 60-120 min | 1-4 Wochen |
Participantsdifferent | 3-8 | Nutzertraffic | 3-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop | Async |
Outputdifferent | North Star metric, Input metric tree, Measurement cadence | Click Data, Interest Signal, Learning Decision | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Experiment results, Decision log, Learning summary |
Tagsno overlap | GrowthMetricsAlignmentRetention | ValidationExperimentsDemandDiscovery | GrowthRetentionConversion | ExperimentsGrowthAnalyticsValidation |