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| Criterion |  Growth Growth Experiment |  Growth Funnel Analysis |  Growth Flywheel |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 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. | 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 Wochen | 1-3 h | 60-120 min | 1-4 Wochen |
Participantsdifferent | 1-6 | 1-5 | 3-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop | Async |
Outputdifferent | Experiment card, Result summary, Next bet | Funnel report, Drop-off analysis, Optimization hypotheses | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Experiment results, Decision log, Learning summary |
Tags1 shared | MarketingGrowthExperimentsLearning | AnalyticsConversionGrowth | GrowthRetentionConversion | ExperimentsGrowthAnalyticsValidation |