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| Criterion |  UX Research Diary Study |  Growth Funnel Analysis |  Operations Failure Mode and Effects Analysis |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | When experiences build up over days or weeks and a single session cannot capture them, Diary Study records the course of everyday life. Recurring triggers, moods, and habits become visible this way, beyond the sharpness of memory. | 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. | For a process, product, or service with noticeable failure risks, the method assesses possible failure modes in advance. It directs attention to combinations of occurrence, effect, and detectability. | 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 | High | High |
Timedifferent | 1-4 Wochen | 1-3 h | 2-6 h | 1-4 Wochen |
Participantsdifferent | 5-20 | 1-5 | 3-10 | 1-6 |
Formatdifferent | Async | Async | Workshop | Async |
Outputdifferent | Diary Entries, Longitudinal Patterns, Experience Timeline | Funnel report, Drop-off analysis, Optimization hypotheses | FMEA Table, Risk Priority, Mitigation Actions | Experiment results, Decision log, Learning summary |
Tagsno overlap | UX researchTrackingBehavior | AnalyticsConversionGrowth | RiskQualityOperationsRoot cause | ExperimentsGrowthAnalyticsValidation |