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| Criterion |  Growth A/B Testing |  UX Research Surveys |  Decision Making Decision Matrix |  Product Discovery Smoke Test |
|---|---|---|---|---|
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 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 several options collide with several criteria, comparison quickly becomes subjective. A Decision Matrix makes the trade-off visible and brings weighting, criteria, and options into a shared logic. | 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 | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 3-14 Tage | 45-90 min | 1-5 Tage |
Participantsdifferent | 1-6 | 50+ | 2-8 | Nutzertraffic |
Formatdifferent | Async | Async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Survey Results, Charts, Segment Insights | Decision Matrix, Scoring Rationale, Selected Option | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | QuantitativeResearchValidation | DecisionCriteriaScoringTradeoffs | ValidationExperimentsDemandGrowth |