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| Criterion | ![]() Product Discovery Hypothesis Prioritization Canvas | ![]() Product Strategy Counter Metrics | ![]() Product Strategy DIBB |
|---|---|---|---|
Purposedifferent | 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. | When a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions. | 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 | Low |
Timedifferent | 60-90 min | 30-60 min | 1-2 h |
Participantsdifferent | 3-8 | 2-6 | 2-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Prioritization Canvas, Hypothesis Backlog | Counter Metric List, Guardrail Definitions | DIBB document, Belief list, Bet list, Learning report |
Tagsno overlap | ExperimentsPrioritizationDiscoveryHypothesis | MetricsMeasurementStrategyExperiments | StrategyDecisionAssumptionsHypothesis |
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