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| Criterion |  Growth Funnel Analysis |  Product Strategy DIBB |  Product Discovery Fake Door Test |  Product Discovery Riskiest Assumption 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. | DIBB helps clarify target groups, value, goals, and priorities by making the logic behind a decision explicit. It captures results as a DIBB document, belief list, bet list, and learning report. | 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. | When an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report. |
Complexitydifferent | Medium | Low | Medium | Medium |
Timedifferent | 1-3 h | 1-2 h | 1-5 Tage | 1-2 Wochen pro Iteration |
Participantsdifferent | 1-5 | 2-8 | Nutzertraffic | 2-6 |
Formatdifferent | Async | Workshop + async | Async | Workshop + async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | DIBB document, Belief list, Bet list, Learning report | Click Data, Interest Signal, Learning Decision | Prioritized Assumption List, Test Plan, Results Report |
Tagsno overlap | AnalyticsConversionGrowth | StrategyDecisionAssumptionsHypothesis | ValidationExperimentsDemandDiscovery | ExperimentsValidationDiscoveryAssumptions |