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| Criterion |  Growth Funnel Analysis |  Growth Growth Experiment |  Product Discovery Riskiest Assumption Test |  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 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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. | 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 Wochen | 1-2 Wochen pro Iteration | 1-4 Wochen |
Participantsdifferent | 1-5 | 1-6 | 2-6 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Experiment card, Result summary, Next bet | Prioritized Assumption List, Test Plan, Results Report | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | MarketingGrowthExperimentsLearning | ExperimentsValidationDiscoveryAssumptions | ExperimentsGrowthAnalyticsValidation |