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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.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.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
HighMediumMediumMedium
Timedifferent
1-4 Wochen1-2 Wochen45-75 min1-5 Tage
Participantsdifferent
1-61-62-8Nutzertraffic
Formatdifferent
AsyncWorkshop + asyncWorkshopAsync
Outputdifferent
Experiment results, Decision log, Learning summaryExperiment card, Result summary, Next betTest Matrix, Test PlanClick Data, Interest Signal, Learning Decision
Tags1 shared
ExperimentsGrowthAnalyticsValidation
MarketingGrowthExperimentsLearning
ExperimentsValidationDiscoveryOptions
ValidationExperimentsDemandDiscovery
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