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| Criterion |  Growth Funnel Analysis |  Product Discovery Assumption Mapping |  Product Strategy DIBB |  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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning 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 | Low | High |
Timedifferent | 1-3 h | 45-60 min | 1-2 h | 1-4 Wochen |
Participantsdifferent | 1-5 | 2-8 | 2-8 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Assumption map, Test backlog, Risk ranking | DIBB document, Belief list, Bet list, Learning report | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | AssumptionsRiskExperimentsValidation | StrategyDecisionAssumptionsHypothesis | ExperimentsGrowthAnalyticsValidation |