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| Criterion |  Product Discovery Smoke Test |  Innovation Design Thinking |  UX Research Surveys |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | 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 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. | 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. |
Complexitydifferent | Low | High | Medium | High |
Timedifferent | 1-5 Tage | 1 Tag bis mehrere Wochen | 3-14 Tage | 1-4 Wochen |
Participantsdifferent | Nutzertraffic | 4-10 | 50+ | 1-6 |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Interest Metrics, Conversion Signal, Learning Note | Problem Statement, Prototype, Test Learnings | Survey Results, Charts, Segment Insights | Experiment results, Decision log, Learning summary |
Tagsno overlap | ValidationExperimentsDemandGrowth | InnovationPrototypeResearch | QuantitativeResearchValidation | ExperimentsGrowthAnalyticsValidation |