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| Criterion |  Growth A/B Testing |  Innovation Design Thinking |  UX Research Affinity Diagramming |  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 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 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. | 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 | High | Low | Low |
Timedifferent | 1-4 Wochen | 1 Tag bis mehrere Wochen | 45–90 min | 1-5 Tage |
Participantsdifferent | 1-6 | 4-10 | 3-10 | Nutzertraffic |
Formatdifferent | Async | Workshop | Workshop | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Problem Statement, Prototype, Test Learnings | Theme clusters, Insight statements, Opportunity areas | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | InnovationPrototypeResearch | SynthesisQualitativeRoot cause | ValidationExperimentsDemandGrowth |