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| Criterion |  Product Strategy Lean Canvas |  Product Strategy ICE Scoring |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When an early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable. | When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas 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 | Medium | Low | Low | High |
Timedifferent | 45-90 min | 30-60 min | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 1-6 | 2-8 | Nutzertraffic | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Async | Async |
Outputdifferent | Lean Canvas, Core Assumptions, Experiment Backlog | ICE Table, Top Idea List | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | StartupLeanAssumptionsBusiness model | PrioritizationScoringGrowthDecision | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |