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| Criterion |  Decision Making Argument Mapping |  UX Research User Interviews |  Product Strategy DIBB |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When statements, evidence, and counterarguments get mixed up, a debate quickly loses its structure. Argument Mapping breaks a thesis down into its reasoning and makes visible what it really rests on. | When teams derive needs only from assumptions and real motives are missing, user interviews give direct access to behavior and meaning. Conversations from the target group's everyday life make patterns, tensions, and open questions solidly visible. | 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 | Low | Low | Low |
Timedifferent | 1-3 h | 30–60 min per interview | 1-2 h | 30-60 min |
Participantsdifferent | 1-8 | 1 participant per interview | 2-8 | 1-5 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Argument Map, Evidence Gaps, Decision Rationale | Interview Notes, Themes, Insight Summary | DIBB document, Belief list, Bet list, Learning report | Completed Experiment Canvas, Success Metric |
Tagsno overlap | SensemakingDecisionRationale | QualitativeResearchCustomerDiscovery | StrategyDecisionAssumptionsHypothesis | ExperimentsValidationDiscoveryHypothesis |