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| Criterion |  Growth Funnel Analysis |  Product Strategy DIBB |  Decision Making Decision Tree |  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. | 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. | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | 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 | 1-2 h | 30-90 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 2-8 | 1-6 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | DIBB document, Belief list, Bet list, Learning report | Decision Tree, Option Map, Assumption List | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | StrategyDecisionAssumptionsHypothesis | DecisionTreeOptions | ExperimentsGrowthAnalyticsValidation |