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| Criterion |  Decision Making Decision Tree |  Growth Funnel Analysis |  Growth A/B Testing |  Product Discovery MVP Test Matrix |
|---|---|---|---|---|
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 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 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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | 30-90 min | 1-3 h | 1-4 Wochen | 45-75 min |
Participantsdifferent | 1-6 | 1-5 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Async | Async | Workshop |
Outputdifferent | Decision Tree, Option Map, Assumption List | Funnel report, Drop-off analysis, Optimization hypotheses | Experiment results, Decision log, Learning summary | Test Matrix, Test Plan |
Tagsno overlap | DecisionTreeOptions | AnalyticsConversionGrowth | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryOptions |