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| Criterion | ![]() UX Research Surveys | ![]() Operations PDCA Cycle | ![]() Growth A/B Testing | ![]() Product Discovery Assumption Mapping |
|---|---|---|---|---|
Purposedifferent | 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. | 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 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Medium | Low | High | Medium |
Timedifferent | 3-14 Tage | 1 h bis mehrere Wochen | 1-4 Wochen | 45-60 min |
Participantsdifferent | 50+ | 1-8 | 1-6 | 2-8 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Survey Results, Charts, Segment Insights | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment results, Decision log, Learning summary | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | QuantitativeResearchValidation | Continuous improvementLeanExperiments | ExperimentsGrowthAnalyticsValidation | AssumptionsRiskExperimentsValidation |



