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| Criterion |  Growth Funnel Analysis |  Product Strategy Lean Canvas |  Operations Root Cause Tree Analysis |  Growth A/B Testing |
|---|---|---|---|---|
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. | 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. | For a problem with several suspected causes, the method builds a causal structure instead of a mere list. It makes visible how causes connect and where the strongest points of leverage lie. | 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 | Medium | Medium | High |
Timedifferent | 1-3 h | 45-90 min | 1-3 h | 1-4 Wochen |
Participantsdifferent | 1-5 | 1-6 | 2-8 | 1-6 |
Formatdifferent | Async | Workshop + async | Workshop | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Lean Canvas, Core Assumptions, Experiment Backlog | Cause Tree, Evidence Notes, Countermeasures | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | StartupLeanAssumptionsBusiness model | Root causeTreeIncidentQuality | ExperimentsGrowthAnalyticsValidation |