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| Criterion |  Growth Growth Experiment |  Decision Making Trade-off Analysis |  Decision Making Constraint Analysis |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | With limited resources, quality, speed, cost, and risk almost always compete with each other. Trade-off Analysis makes these tensions explicit and prevents decisions from producing hidden side effects. | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | 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 | 1-2 Wochen | 45-120 min | 30-90 min | 1-4 Wochen |
Participantsdifferent | 1-6 | 2-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment card, Result summary, Next bet | Trade-off Matrix, Criteria List, Decision Rationale, Accepted Downsides | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Experiment results, Decision log, Learning summary |
Tagsno overlap | MarketingGrowthExperimentsLearning | TradeoffsDecisionCriteriaOptions | ConstraintsDecisionPlanningOptions | ExperimentsGrowthAnalyticsValidation |