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| Criterion |  Growth Funnel Analysis |  Operations ABC Analysis |  Product Discovery Experiment Canvas |  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. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | 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 | Low | Low | High |
Timedifferent | 1-3 h | 30-60 min | 30-60 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 1-5 | 1-5 | 1-6 |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | ABC Classification, Focus Rules, Control List | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | PrioritizationOperationsPortfolio | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |