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Criterion
A paper-based illustration representing WSJF with its core stages and visible working result.
Agile
WSJF
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 for Fake Door Test
Product Discovery
Fake Door Test
Purposedifferent
When many tasks compete for the same capacity, it orders work by economic impact. It makes time lost, benefit, and effort comparable together.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 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.
Complexitydifferent
HighHighLowMedium
Timedifferent
45-90 min1-4 Wochen30-60 min1-5 Tage
Participantsdifferent
3-101-61-5Nutzertraffic
Formatdifferent
WorkshopAsyncWorkshop + asyncAsync
Outputdifferent
Ranked Backlog, Cost-of-Delay AssumptionsExperiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success MetricClick Data, Interest Signal, Learning Decision
Tagsno overlap
LeanEconomicsSequencePrioritization
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
ValidationExperimentsDemandDiscovery
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