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| Criterion |  UX Research Affinity Diagramming |  Innovation Design Thinking |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | When research notes, feedback, or observations sit unconnected side by side, affinity diagramming sorts the raw material into solid themes. Many individual points turn into patterns that make decisions and opportunities clearer. | For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service. | 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 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 | Low | High | High | Low |
Timedifferent | 45–90 min | 1 Tag bis mehrere Wochen | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 3-10 | 4-10 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop | Workshop | Async | Async |
Outputdifferent | Theme clusters, Insight statements, Opportunity areas | Problem Statement, Prototype, Test Learnings | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | SynthesisQualitativeRoot cause | InnovationPrototypeResearch | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |