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| Criterion |  Decision Making Decision Tree |  Growth A/B Testing |  Product Discovery Concierge MVP |  Product Discovery Learning Card |
|---|---|---|---|---|
Purposedifferent | 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. | When an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible. |
Complexitydifferent | Medium | High | Medium | Low |
Timedifferent | 30-90 min | 1-4 Wochen | 1-4 Wochen | 25-40 min |
Participantsdifferent | 1-6 | 1-6 | 3-10 Kunden | 1-5 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Experiment results, Decision log, Learning summary | Concierge Learnings, Service Blueprint, MVP Risks | Learning Card with evidence and next action |
Tagsno overlap | DecisionTreeOptions | ExperimentsGrowthAnalyticsValidation | MVPValidationServiceDiscovery | ExperimentsValidationDiscoveryLearning |