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| Criterion |  Product Strategy DIBB |  Growth Growth Experiment |  Product Discovery Assumption Mapping |  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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | 1-2 Wochen | 45-60 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 1-6 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Experiment card, Result summary, Next bet | Assumption map, Test backlog, Risk ranking | Experiment results, Decision log, Learning summary |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | MarketingGrowthExperimentsLearning | AssumptionsRiskExperimentsValidation | ExperimentsGrowthAnalyticsValidation |