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| Criterion |  Growth A/B Testing |  Decision Making Decision Tree |  Product Discovery Experiment Canvas |  Product Discovery Test Card |
|---|---|---|---|---|
Purposedifferent | 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. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success. |
Complexitydifferent | High | Medium | Low | Low |
Timedifferent | 1-4 Wochen | 30-90 min | 30-60 min | 20-35 min |
Participantsdifferent | 1-6 | 1-6 | 1-5 | 1-5 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Decision Tree, Option Map, Assumption List | Completed Experiment Canvas, Success Metric | Test Card with a pre-set threshold |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | DecisionTreeOptions | ExperimentsValidationDiscoveryHypothesis | ExperimentsValidationDiscoveryHypothesis |