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| Criterion |  UX Research Card Sorting |  Product Strategy DIBB |  Product Discovery Assumption Mapping |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When content only makes sense internally and users can't find the structure again, card sorting exposes their mental order. Terms, groups, and naming are then aligned with the target group's expectations. | 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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first. | 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 | Low | Low | Medium | Low |
Timedifferent | 20-45 min | 1-2 h | 45-60 min | 30-60 min |
Participantsdifferent | Based on research question | 2-8 | 2-8 | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Content groups, Label set, IA hypotheses | DIBB document, Belief list, Bet list, Learning report | Assumption map, Test backlog, Risk ranking | Completed Experiment Canvas, Success Metric |
Tagsno overlap | Information architectureNavigationStructure | StrategyDecisionAssumptionsHypothesis | AssumptionsRiskExperimentsValidation | ExperimentsValidationDiscoveryHypothesis |