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| Criterion |  Growth A/B Testing |  Growth Growth Experiment |  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 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. |
Complexitydifferent | High | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-2 Wochen | 1-3 h |
Participantsdifferent | 1-6 | 1-6 | 1-5 |
Formatdifferent | Async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Experiment card, Result summary, Next bet | Funnel report, Drop-off analysis, Optimization hypotheses |
Tags1 shared | ExperimentsGrowthAnalyticsValidation | MarketingGrowthExperimentsLearning | AnalyticsConversionGrowth |
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