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Criterion
Paper illustration of ICE Scoring with its method-specific working model.
Product Strategy
ICE Scoring
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration of Cost of Delay with its method-specific working model.
Delivery
Cost of Delay
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.When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.Helps clarify scope, order, and delivery flow in concrete terms. It makes work, constraints, and sequence manageable. The result is captured as a Cost of Delay table and prioritization sequence.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
LowMediumHighHigh
Timedifferent
30-60 min1-2 Wochen90-180 min1-4 Wochen
Participantsdifferent
2-81-63-81-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopAsync
Outputdifferent
ICE Table, Top Idea ListExperiment card, Result summary, Next betCoD Table, Prioritization SequenceExperiment results, Decision log, Learning summary
Tagsno overlap
PrioritizationScoringGrowthDecision
MarketingGrowthExperimentsLearning
PrioritizationDeliveryEconomicsDecision
ExperimentsGrowthAnalyticsValidation
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