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| Criterion |  UX Research Tree Testing |  Innovation Design Sprint |  Growth A/B Testing |  Product Discovery Smoke Test |
|---|---|---|---|---|
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. | When the product question is unclear and time pressure is high, the method takes a team from an open idea to a testable solution. It connects problem understanding, decision, and learning in one compact format, lowering the risk of spending a lot of energy on a mere guess. | 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Medium | High | High | Low |
Timedifferent | 1-2 Tage | 4-5 Tage | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | Based on research question | 5-8 | 1-6 | Nutzertraffic |
Formatdifferent | Async | Workshop | Async | Async |
Outputdifferent | Findability Metrics, Path Analysis, Revised IA | Prototype, Test Findings, Decision Rationale | Experiment results, Decision log, Learning summary | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | Information architectureNavigationFindability | Design sprintPrototypeValidationInnovation | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandGrowth |