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| Criterion |  Product Discovery Opportunity Scoring |  Product Discovery Jobs to Be Done |  Product Strategy DIBB |  Product Discovery Hypothesis Prioritization Canvas |
|---|---|---|---|---|
Purposedifferent | When opportunities need ranking by their effect, it makes importance and satisfaction directly comparable. It separates problem, assumption, solution, and evidence. The result is captured as an opportunity-score table and top outcomes. | When switching motives and progress are unclear, it reconstructs the situation from real customer circumstances. It shows why a switch happens and what kind of progress is being sought. | 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 hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. |
Complexitydifferent | Medium | Medium | Low | Medium |
Timedifferent | 60-120 min | 1-3 Wochen | 1-2 h | 60-90 min |
Participantsdifferent | 3-6 | 5-12 Interviews | 2-8 | 3-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Opportunity Score Table, Top Outcomes | Job Stories, Outcome Statements, Opportunity List | DIBB document, Belief list, Bet list, Learning report | Prioritization Canvas, Hypothesis Backlog |
Tagsno overlap | PrioritizationDiscoveryOutcomesNeeds | CustomerOutcomesNeeds | StrategyDecisionAssumptionsHypothesis | ExperimentsPrioritizationDiscoveryHypothesis |