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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Gap Analysis method illustration showing its working structure
Business Strategy
GAP Analysis
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
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.GAP Analysis compares the current state with a target picture and makes the distance manageable. It becomes useful when, ahead of new initiatives, it must become clear which capabilities, processes, or resources are missing.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 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.
Complexitydifferent
HighMediumMediumMedium
Timedifferent
1-4 Wochen1-3 h1-5 Tage45-75 min
Participantsdifferent
1-62-8Nutzertraffic2-8
Formatdifferent
AsyncWorkshop + asyncAsyncWorkshop
Outputdifferent
Experiment results, Decision log, Learning summaryGap Matrix, Action Plan, Risk NotesClick Data, Interest Signal, Learning DecisionTest Matrix, Test Plan
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
StrategyAnalysisPlanning
ValidationExperimentsDemandDiscovery
ExperimentsValidationDiscoveryOptions
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