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| Criterion |  Growth Funnel Analysis |  Product Discovery Concierge MVP |  Product Strategy DIBB |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
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. | 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 experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Medium | Medium | Low | Low |
Timedifferent | 1-3 h | 1-4 Wochen | 1-2 h | 30-60 min |
Participantsdifferent | 1-5 | 3-10 Kunden | 2-8 | 1-5 |
Formatdifferent | Async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Funnel report, Drop-off analysis, Optimization hypotheses | Concierge Learnings, Service Blueprint, MVP Risks | DIBB document, Belief list, Bet list, Learning report | Completed Experiment Canvas, Success Metric |
Tagsno overlap | AnalyticsConversionGrowth | MVPValidationServiceDiscovery | StrategyDecisionAssumptionsHypothesis | ExperimentsValidationDiscoveryHypothesis |