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| Criterion |  Growth A/B Testing |  UX Research Tree Testing |  UX Research Card Sorting |  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 a navigation exists but search paths still fail, tree testing checks findability without visual distraction. The method shows whether labels, levels, and paths really lead to the intended destination. | When content only makes sense internally and users can't find the structure again, card sorting exposes their mental order. Terms, groups, and naming are then aligned with the target group's expectations. | 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 | Low | Low |
Timedifferent | 1-4 Wochen | 1-2 Tage | 20-45 min | 30-60 min |
Participantsdifferent | 1-6 | Based on research question | Based on research question | 1-5 |
Formatdifferent | Async | Async | Workshop + async | Workshop + async |
Outputdifferent | Experiment results, Decision log, Learning summary | Findability Metrics, Path Analysis, Revised IA | Content groups, Label set, IA hypotheses | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | Information architectureNavigationFindability | Information architectureNavigationStructure | ExperimentsValidationDiscoveryHypothesis |