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Criterion
Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
When many tasks need to be classified quickly, it sorts them by perceived effort and similarity. It reduces the effort of fine-grained estimation for large volumes.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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.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
MediumHighMediumLow
Timedifferent
30-90 min1-4 Wochen1-2 Wochen pro Iteration30-60 min
Participantsdifferent
3-121-62-61-5
Formatdifferent
WorkshopAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Affinity Size Map, Grouped Estimates, Unclear ItemsExperiment results, Decision log, Learning summaryPrioritized Assumption List, Test Plan, Results ReportCompleted Experiment Canvas, Success Metric
Tagsno overlap
EstimationBacklogRelative sizing
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryAssumptions
ExperimentsValidationDiscoveryHypothesis
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