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| Criterion |  Decision Making Delphi Method |  Growth Funnel Analysis |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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 | High | Medium | Low | High |
Timedifferent | 1-4 Wochen | 1-3 h | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 6-30 Experten | 1-5 | Nutzertraffic | 1-6 |
Formatsame | Async | Async | Async | Async |
Outputdifferent | Expert Forecast, Consensus Range, Assumption Notes | Funnel report, Drop-off analysis, Optimization hypotheses | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | ForecastingExpertsDecisionStrategy | AnalyticsConversionGrowth | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |