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| Criterion |  Growth Funnel Analysis |  Product Discovery Concierge MVP |  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 an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | 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 | 3-10 Kunden | 1-6 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Async | Async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Concierge Learnings, Service Blueprint, MVP Risks | Experiment results, Decision log, Learning summary | Click Data, Interest Signal, Learning Decision |
Tagsno overlap | AnalyticsConversionGrowth | MVPValidationServiceDiscovery | ExperimentsGrowthAnalyticsValidation | ValidationExperimentsDemandDiscovery |