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| Criterion |  Growth A/B Testing |  Product Discovery Smoke Test |  UX Research Surveys |  Growth Funnel Analysis |
|---|---|---|---|---|
Purposedifferent | 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. | When a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal. | 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. |
Complexitydifferent | High | Low | Medium | Medium |
Timedifferent | 1-4 Wochen | 1-5 Tage | 3-14 Tage | 1-3 h |
Participantsdifferent | 1-6 | Nutzertraffic | 50+ | 1-5 |
Formatsame | Async | Async | Async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note | Survey Results, Charts, Segment Insights | Funnel report, Drop-off analysis, Optimization hypotheses |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth | QuantitativeResearchValidation | AnalyticsConversionGrowth |