View methods side by side.
Choose up to four methods. Add them using the search and share the comparison by copying its link.
| Criterion |  Product Strategy DIBB |  Growth A/B Testing |  Product Strategy Counter Metrics |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | 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 two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. | 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. | 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 | High | Low | Low |
Timedifferent | 1-2 h | 1-4 Wochen | 30-60 min | 30-60 min |
Participantsdifferent | 2-8 | 1-6 | 2-6 | 1-5 |
Formatdifferent | Workshop + async | Async | Workshop + async | Workshop + async |
Outputdifferent | DIBB document, Belief list, Bet list, Learning report | Experiment results, Decision log, Learning summary | Counter Metric List, Guardrail Definitions | Completed Experiment Canvas, Success Metric |
Tagsno overlap | StrategyDecisionAssumptionsHypothesis | ExperimentsGrowthAnalyticsValidation | MetricsMeasurementStrategyExperiments | ExperimentsValidationDiscoveryHypothesis |