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| Criterion |  Product Strategy DIBB |  Growth Funnel Analysis |  Product Discovery Riskiest Assumption Test |  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. | When an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result 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 | Low | Medium | Medium | High |
Timedifferent | 1-2 h | 1-3 h | 1-2 Wochen pro Iteration | 1-4 Wochen |
Participantsdifferent | 2-8 | 1-5 | 2-6 | 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 | Prioritized Assumption List, Test Plan, Results Report | Experiment results, Decision log, Learning summary |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | AnalyticsConversionGrowth | ExperimentsValidationDiscoveryAssumptions | ExperimentsGrowthAnalyticsValidation |