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| Criterion |  Growth A/B Testing |  Operations 5 Whys |  Operations PDCA Cycle |  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. | For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | 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 | 15-30 min | 1 h bis mehrere Wochen | 1-5 Tage |
Participantsdifferent | 1-6 | 2-6 | 1-8 | Nutzertraffic |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Root cause notes, Countermeasures | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Root causeIncidentLeanProblem solving | Continuous improvementLeanExperiments | ValidationExperimentsDemandGrowth |