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Criterion
Paper illustration of Cost of Delay with its method-specific working model.
Delivery
Cost of Delay
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.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 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
HighLowMediumHigh
Timedifferent
90-180 min1-5 Tage1-5 Tage1-4 Wochen
Participantsdifferent
3-8NutzertrafficNutzertraffic1-6
Formatdifferent
WorkshopAsyncAsyncAsync
Outputdifferent
CoD Table, Prioritization SequenceInterest Metrics, Conversion Signal, Learning NoteClick Data, Interest Signal, Learning DecisionExperiment results, Decision log, Learning summary
Tagsno overlap
PrioritizationDeliveryEconomicsDecision
ValidationExperimentsDemandGrowth
ValidationExperimentsDemandDiscovery
ExperimentsGrowthAnalyticsValidation
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