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| Criterion |  Product Strategy DIBB |  Growth Funnel Analysis |  Decision Making Assumption Surfacing |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 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. | Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it. | 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 | Low | Medium | Low | High |
Timedifferent | 1-2 h | 1-3 h | 45-90 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 1-5 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Funnel report, Drop-off analysis, Optimization hypotheses | Assumption List, Critical Assumptions, Learning Plan | Experiment results, Decision log, Learning summary |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | AnalyticsConversionGrowth | AssumptionsRiskDecisionDiscovery | ExperimentsGrowthAnalyticsValidation |