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| Criterion |  Growth Funnel Analysis |  Operations ABC Analysis |  Product Strategy RICE Scoring |  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 many initiatives compete for the same resources, it brings reach, impact, confidence, and effort into one shared ranking. It makes prioritization economically connectable. | 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 | Medium | High |
Timedifferent | 1-3 h | 30-60 min | 60-90 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 1-5 | 2-10 | 1-6 |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | ABC Classification, Focus Rules, Control List | RICE Scores, Ranked List, Assumption Log | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | PrioritizationOperationsPortfolio | PrioritizationScoringRoadmapTradeoffs | ExperimentsGrowthAnalyticsValidation |