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| Criterion |  Innovation Design Thinking |  Decision Making Risk Matrix |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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 project faces many possible disruptions, it quickly becomes unclear which risks deserve attention first. It separates options, evaluation criteria, and open risks. The result is captured as a Risk Matrix and a Top Risk List. | 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. | 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 | High | Low | Low | High |
Timedifferent | 1 Tag bis mehrere Wochen | 30-60 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 4-10 | 3-10 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Workshop + async | Async | Async |
Outputdifferent | Problem Statement, Prototype, Test Learnings | Risk Matrix, Top Risk List | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | InnovationPrototypeResearch | RiskDecisionPrioritizationAssessment | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |