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| Criterion |  Growth Funnel Analysis |  UX Research Diary Study |  Growth A/B Testing |  Product Discovery Fake Door Test |
|---|---|---|---|---|
Purposedifferent | 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. | 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 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 is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small. |
Complexitydifferent | Medium | Medium | High | Medium |
Timedifferent | 1-3 h | 1-4 Wochen | 1-4 Wochen | 1-5 Tage |
Participantsdifferent | 1-5 | 5-20 | 1-6 | Nutzertraffic |
Formatsame | Async | Async | Async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Diary Entries, Longitudinal Patterns, Experience Timeline | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | AnalyticsConversionGrowth | UX researchTrackingBehavior | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery |