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| Criterion |  Growth A/B Testing |  Decision Making Pareto Analysis |  Operations Fishbone Diagram |  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. | In many problem situations, effect is distributed unequally across many causes. A Pareto Analysis separates the few drivers with high leverage from the long remainder and focuses attention on what measurably moves the needle. | When a problem has several possible contributing factors, the method sorts causes by cause areas. It prevents an initial hunch from blocking the view of other plausible drivers. | 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 | Low | Low | Low |
Timedifferent | 1-4 Wochen | 30-60 min | 30-60 min | 1-5 Tage |
Participantsdifferent | 1-6 | 1-6 | 2-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Pareto Chart, Top Causes, Focus List | Fishbone Diagram, Cause Categories, Investigation Backlog | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | PrioritizationQualityFocusRoot cause | Root causeQualityOperations | ValidationExperimentsDemandGrowth |