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| Criterion |  Growth A/B Testing |  Operations PDCA Cycle |  Growth Funnel Analysis |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
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 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 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | High | Low | Medium | Medium |
Timedifferent | 1-4 Wochen | 1 h bis mehrere Wochen | 1-3 h | 45-60 min |
Participantsdifferent | 1-6 | 1-8 | 1-5 | 2-8 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Funnel report, Drop-off analysis, Optimization hypotheses | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Continuous improvementLeanExperiments | AnalyticsConversionGrowth | AssumptionsRiskExperimentsValidation |