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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it.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
HighMediumLowLow
Timedifferent
1-4 Wochen45-75 min45-90 min30-60 min
Participantsdifferent
1-62-82-81-5
Formatdifferent
AsyncWorkshopWorkshop + asyncWorkshop + async
Outputdifferent
Experiment results, Decision log, Learning summaryTest Matrix, Test PlanAssumption List, Critical Assumptions, Learning PlanCompleted Experiment Canvas, Success Metric
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryOptions
AssumptionsRiskDecisionDiscovery
ExperimentsValidationDiscoveryHypothesis
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