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| Criterion |  Growth A/B Testing |  Product Discovery Outcome-Driven Innovation |  Product Discovery Smoke Test |  Innovation Design Sprint |
|---|---|---|---|---|
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. | Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs. | 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 the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. |
Complexitydifferent | High | High | Low | High |
Timedifferent | 1-4 Wochen | Mehrere Wochen | 1-5 Tage | 4-5 Tage |
Participantsdifferent | 1-6 | 2-6 researchers plus sample | Nutzertraffic | 5-8 |
Formatdifferent | Async | Workshop + async | Async | Workshop |
Outputdifferent | Experiment results, Decision log, Learning summary | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Interest Metrics, Conversion Signal, Learning Note | Prototype, Test Findings, Decision Rationale |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | OutcomesInnovationResearchQuantitative | ValidationExperimentsDemandGrowth | Design sprintPrototypeValidationInnovation |