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| Criterion |  Growth Funnel Analysis |  Product Discovery Hypothesis Prioritization Canvas |  Operations ABC Analysis |  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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | With many similar objects of differing economic significance, the method prioritizes effort by effect. It separates what needs regular steering from what rarely needs attention. | 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 | 1-3 h | 60-90 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 3-8 | 1-5 | 1-6 |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Prioritization Canvas, Hypothesis Backlog | ABC Classification, Focus Rules, Control List | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | ExperimentsPrioritizationDiscoveryHypothesis | PrioritizationOperationsPortfolio | ExperimentsGrowthAnalyticsValidation |