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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 for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment 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 demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.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.
Complexitydifferent
LowHighMediumLow
Timedifferent
30-60 min1-4 Wochen1-5 Tage30-60 min
Participantsdifferent
2-81-6Nutzertraffic1-5
Formatdifferent
Workshop + asyncAsyncAsyncWorkshop + async
Outputdifferent
ICE Table, Top Idea ListExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionCompleted Experiment Canvas, Success Metric
Tagsno overlap
PrioritizationScoringGrowthDecision
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
ExperimentsValidationDiscoveryHypothesis
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