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| Criterion | ![]() Product Discovery Solution Interview | ![]() Product Strategy DIBB | ![]() Decision Making Delphi Method | ![]() Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | When a solution idea is already on the table, it checks how it is understood and evaluated. It looks for resonance, objections, and missing fit early in the conversation. | 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 knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer 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. |
Complexitydifferent | Medium | Low | High | Low |
Timedifferent | 30-60 min je Interview | 1-2 h | 1-4 Wochen | 30-60 min |
Participantsdifferent | 5-10 Interviews | 2-8 | 6-30 Experten | 1-5 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | Solution Feedback, Objection List, Validation Notes | DIBB document, Belief list, Bet list, Learning report | Expert Forecast, Consensus Range, Assumption Notes | Completed Experiment Canvas, Success Metric |
Tagsno overlap | ValidationInterviewsPrototype | StrategyDecisionAssumptionsHypothesis | ForecastingExpertsDecisionStrategy | ExperimentsValidationDiscoveryHypothesis |



