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| Criterion |  Product Discovery Jobs to Be Done |  Growth A/B Testing |  Growth Funnel Analysis |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When switching motives and progress are unclear, it reconstructs the situation from real customer circumstances. It shows why a switch happens and what kind of progress is being sought. | 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 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 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. |
Complexitydifferent | Medium | High | Medium | Low |
Timedifferent | 1-3 Wochen | 1-4 Wochen | 1-3 h | 30-60 min |
Participantsdifferent | 5-12 Interviews | 1-6 | 1-5 | 1-5 |
Formatdifferent | Workshop + async | Async | Async | Workshop + async |
Outputdifferent | Job Stories, Outcome Statements, Opportunity List | Experiment results, Decision log, Learning summary | Funnel report, Drop-off analysis, Optimization hypotheses | Completed Experiment Canvas, Success Metric |
Tagsno overlap | CustomerOutcomesNeeds | ExperimentsGrowthAnalyticsValidation | AnalyticsConversionGrowth | ExperimentsValidationDiscoveryHypothesis |