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Criterion
Paper illustration of ICE Scoring with its method-specific working model.
Product Strategy
ICE Scoring
Paper illustration of Cost of Delay with its method-specific working model.
Delivery
Cost of Delay
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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.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 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.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
LowHighLowHigh
Timedifferent
30-60 min90-180 min30-60 min1-4 Wochen
Participantsdifferent
2-83-81-51-6
Formatdifferent
Workshop + asyncWorkshopWorkshop + asyncAsync
Outputdifferent
ICE Table, Top Idea ListCoD Table, Prioritization SequenceCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summary
Tagsno overlap
PrioritizationScoringGrowthDecision
PrioritizationDeliveryEconomicsDecision
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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