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| Criterion |  Product Strategy Lean Canvas |  Growth Funnel Analysis |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
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 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. | 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 | Medium | High | Low |
Timedifferent | 45-90 min | 1-3 h | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-6 | 1-5 | 1-6 | Nutzertraffic |
Formatdifferent | Workshop + async | Async | Async | Async |
Outputdifferent | Lean Canvas, Core Assumptions, Experiment Backlog | Funnel report, Drop-off analysis, Optimization hypotheses | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | StartupLeanAssumptionsBusiness model | AnalyticsConversionGrowth | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |