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| Criterion |  Product Strategy DIBB |  Growth Funnel Analysis |  Product Discovery Experiment Canvas |  Product Discovery Assumption Mapping |
|---|---|---|---|---|
Purposedifferent | 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 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 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. | When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. |
Complexitydifferent | Low | Medium | Low | Medium |
Timedifferent | 1-2 h | 1-3 h | 30-60 min | 45-60 min |
Participantsdifferent | 2-8 | 1-5 | 1-5 | 2-8 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Funnel report, Drop-off analysis, Optimization hypotheses | Completed Experiment Canvas, Success Metric | Assumption map, Test backlog, Risk ranking |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | AnalyticsConversionGrowth | ExperimentsValidationDiscoveryHypothesis | AssumptionsRiskExperimentsValidation |