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Criterion
Paper illustration of ICE Scoring with its method-specific working model.
Product Strategy
ICE Scoring
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
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list.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.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
LowLowLowHigh
Timedifferent
30-60 min1-2 h20-35 min1-4 Wochen
Participantsdifferent
2-82-81-51-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
ICE Table, Top Idea ListDIBB document, Belief list, Bet list, Learning reportTest Card with a pre-set thresholdExperiment results, Decision log, Learning summary
Tagsno overlap
PrioritizationScoringGrowthDecision
StrategyDecisionAssumptionsHypothesis
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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