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| Criterion |  Growth Funnel Analysis |  Innovation Design Thinking |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses. | 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 | Medium | High | High | Low |
Timedifferent | 1-3 h | 1 Tag bis mehrere Wochen | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-5 | 4-10 | 1-6 | Nutzertraffic |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Problem Statement, Prototype, Test Learnings | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | AnalyticsConversionGrowth | InnovationPrototypeResearch | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |