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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
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.For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.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
HighMediumLowMedium
Timedifferent
1-4 Wochen30-90 min25-40 min45-75 min
Participantsdifferent
1-61-61-52-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop
Outputdifferent
Experiment results, Decision log, Learning summaryDecision Tree, Option Map, Assumption ListLearning Card with evidence and next actionTest Matrix, Test Plan
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
DecisionTreeOptions
ExperimentsValidationDiscoveryLearning
ExperimentsValidationDiscoveryOptions
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