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| Criterion |  Growth Funnel Analysis |  Growth A/B Testing |  Agile Affinity Estimation |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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 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 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 | Medium | Low |
Timedifferent | 1-3 h | 1-4 Wochen | 30-90 min | 1-5 Tage |
Participantsdifferent | 1-5 | 1-6 | 3-12 | Nutzertraffic |
Formatdifferent | Async | Async | Workshop | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Experiment results, Decision log, Learning summary | Affinity Size Map, Grouped Estimates, Unclear Items | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | AnalyticsConversionGrowth | ExperimentsGrowthAnalyticsValidation | EstimationBacklogRelative sizing | ValidationExperimentsDemandGrowth |