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| Criterion |  Architecture Quality Attribute Workshop |  UX Research Tree Testing |  Product Discovery Smoke Test |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | A Quality Attribute Workshop translates quality requirements into concrete scenarios and architecture impulses. The method brings product, engineering, and operations to the same view of desired properties. | 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. | 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. |
Complexitydifferent | Medium | Medium | Low | High |
Timedifferent | 2-4 h | 1-2 Tage | 1-5 Tage | 1-4 Wochen |
Participantsdifferent | 5-15 | Based on research question | Nutzertraffic | 1-6 |
Formatdifferent | Workshop | Async | Async | Async |
Outputdifferent | Quality Scenarios, Priority List, Architecture Concerns | Findability Metrics, Path Analysis, Revised IA | Interest Metrics, Conversion Signal, Learning Note | Experiment results, Decision log, Learning summary |
Tagsno overlap | RequirementsArchitectureWorkshop | Information architectureNavigationFindability | ValidationExperimentsDemandGrowth | ExperimentsGrowthAnalyticsValidation |