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Criterion
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration of a Test Card with four fields for hypothesis, test, metric, and success threshold.
Product Discovery
Test Card
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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 many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success.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.
Complexitydifferent
LowMediumLowHigh
Timedifferent
1-2 h1-3 h20-35 min1-4 Wochen
Participantsdifferent
2-81-51-51-6
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
DIBB document, Belief list, Bet list, Learning reportFunnel report, Drop-off analysis, Optimization hypothesesTest Card with a pre-set thresholdExperiment results, Decision log, Learning summary
Tagsno overlap
StrategyDecisionAssumptionsHypothesis
AnalyticsConversionGrowth
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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