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| Criterion |  Growth A/B Testing |  Growth Funnel Analysis |  Product Discovery Landing Page Test |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | 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 a value proposition first needs to be checked for resonance, it condenses the idea onto a focused entry page. It shows whether language and offering carry interest. | 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 | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 1-3 h | 1-5 Tage | 30-60 min |
Participantsdifferent | 1-6 | 1-5 | Nutzertraffic | 1-5 |
Formatdifferent | Async | Async | Async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Funnel report, Drop-off analysis, Optimization hypotheses | Landing Page, Conversion Data, Learning Summary | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | AnalyticsConversionGrowth | ValidationConversionMarketing | ExperimentsValidationDiscoveryHypothesis |