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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration of a Test Card with four fields for hypothesis, test, metric, and success threshold.
Product Discovery
Test Card
Purposedifferent
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 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.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.The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success.
Complexitydifferent
HighLowLowLow
Timedifferent
1-4 Wochen30-60 min1-2 h20-35 min
Participantsdifferent
1-61-52-81-5
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success MetricDIBB document, Belief list, Bet list, Learning reportTest Card with a pre-set threshold
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryHypothesis
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