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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 for DACI
Decision Making
DACI
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
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.In cross-functional decisions, responsibilities quickly blur between approval, influence, and execution. DACI arranges these roles so decision pressure, contribution, and information stay cleanly separated.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
HighMediumLowMedium
Timedifferent
1-4 Wochen45-75 min30-60 min1-5 Tage
Participantsdifferent
1-62-82-10Nutzertraffic
Formatdifferent
AsyncWorkshopWorkshop + asyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryTest Matrix, Test PlanDACI Matrix, Decision Owner, Decision LogClick Data, Interest Signal, Learning Decision
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryOptions
DecisionRolesGovernanceAlignment
ValidationExperimentsDemandDiscovery
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