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| Criterion |  Growth Funnel Analysis |  Engineering Failure Scenario Analysis |  Product Discovery Experiment Canvas |  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. | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. | 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 | Low | High |
Timedifferent | 1-3 h | 1-3 h | 30-60 min | 1-4 Wochen |
Participantsdifferent | 1-5 | 3-8 | 1-5 | 1-6 |
Formatdifferent | Async | Workshop | Workshop + async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | AnalyticsConversionGrowth | FailureResilienceRisk | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |