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| Criterion |  Decision Making Decision Tree |  Decision Making Delphi Method |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together. | 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Medium | High | High | Low |
Timedifferent | 30-90 min | 1-4 Wochen | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-6 | 6-30 Experten | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Async | Async | Async |
Outputdifferent | Decision Tree, Option Map, Assumption List | Expert Forecast, Consensus Range, Assumption Notes | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | DecisionTreeOptions | ForecastingExpertsDecisionStrategy | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |