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| Criterion |  Product Strategy Value Proposition Canvas |  Product Discovery Experiment Canvas |  Product Discovery Assumption Mapping |  Product Strategy DIBB |
|---|---|---|---|---|
Purposedifferent | When the value proposition and customer expectation drift apart, it makes fit and mismatch legible. It shows where offering and need don't yet come together. | 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. | 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. |
Complexitydifferent | Medium | Low | Medium | Low |
Timedifferent | 1-2 h | 30-60 min | 45-60 min | 1-2 h |
Participantsdifferent | 2-8 | 1-5 | 2-8 | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Value Proposition Canvas, Fit Gaps, Hypotheses | Completed Experiment Canvas, Success Metric | Assumption map, Test backlog, Risk ranking | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ValueNeedsStrategy | ExperimentsValidationDiscoveryHypothesis | AssumptionsRiskExperimentsValidation | StrategyDecisionAssumptionsHypothesis |