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Criterion
Paper illustration of ICE Scoring with its method-specific working model.
Product Strategy
ICE Scoring
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 Hypothesis Prioritization Canvas with a method-specific labelled workspace.
Product Discovery
Hypothesis Prioritization Canvas
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 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.When many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog.
Complexitydifferent
LowHighLowMedium
Timedifferent
30-60 min1-4 Wochen30-60 min60-90 min
Participantsdifferent
2-81-61-53-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop
Outputdifferent
ICE Table, Top Idea ListExperiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success MetricPrioritization Canvas, Hypothesis Backlog
Tagsno overlap
PrioritizationScoringGrowthDecision
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
ExperimentsPrioritizationDiscoveryHypothesis
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