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| Criterion |  Product Discovery Assumption Mapping |  Innovation Design Thinking |  UX Research Surveys |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | Medium | High | Medium | High |
Timedifferent | 45-60 min | 1 Tag bis mehrere Wochen | 3-14 Tage | 1-4 Wochen |
Participantsdifferent | 2-8 | 4-10 | 50+ | 1-6 |
Formatdifferent | Workshop + async | Workshop | Async | Async |
Outputdifferent | Assumption map, Test backlog, Risk ranking | Problem Statement, Prototype, Test Learnings | Survey Results, Charts, Segment Insights | Experiment results, Decision log, Learning summary |
Tagsno overlap | AssumptionsRiskExperimentsValidation | InnovationPrototypeResearch | QuantitativeResearchValidation | ExperimentsGrowthAnalyticsValidation |