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| Criterion |  UX Research Tree Testing |  Operations PDCA Cycle |  Growth A/B Testing |  UX Research Card Sorting |
|---|---|---|---|---|
Purposedifferent | 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. | For an improvement that still has to prove itself in everyday work, the method runs it through small learning loops. It connects planning, checking, and standardization into a repeatable learning mode. | 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 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. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | 1-2 Tage | 1 h bis mehrere Wochen | 1-4 Wochen | 20-45 min |
Participantsdifferent | Based on research question | 1-8 | 1-6 | Based on research question |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Findability Metrics, Path Analysis, Revised IA | PDCA Log, Experiment Plan, Learning Outcome, Standard Change | Experiment results, Decision log, Learning summary | Content groups, Label set, IA hypotheses |
Tagsno overlap | Information architectureNavigationFindability | Continuous improvementLeanExperiments | ExperimentsGrowthAnalyticsValidation | Information architectureNavigationStructure |