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| Criterion |  Growth Funnel Analysis |  Growth A/B Testing |  UX Research Surveys |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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 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 a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal. | 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 h | 1-4 Wochen | 3-14 Tage | 30-60 min |
Participantsdifferent | 1-5 | 1-6 | 50+ | 1-5 |
Formatdifferent | Async | Async | Async | Workshop + async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Experiment results, Decision log, Learning summary | Survey Results, Charts, Segment Insights | Completed Experiment Canvas, Success Metric |
Tagsno overlap | AnalyticsConversionGrowth | ExperimentsGrowthAnalyticsValidation | QuantitativeResearchValidation | ExperimentsValidationDiscoveryHypothesis |