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| Criterion |  Agile Affinity Estimation |  Decision Making Delphi Method |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes. | 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 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 | Medium | High | Low | High |
Timedifferent | 30-90 min | 1-4 Wochen | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 3-12 | 6-30 Experten | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Async | Async | Async |
Outputdifferent | Affinity Size Map, Grouped Estimates, Unclear Items | Expert Forecast, Consensus Range, Assumption Notes | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | EstimationBacklogRelative sizing | ForecastingExpertsDecisionStrategy | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |