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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
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 a Learning Card with four fields for hypothesis, observation, insight, and action.
Product Discovery
Learning Card
Purposedifferent
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.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.The Learning Card connects traceable test results to a reasoned next action while keeping the limits of the insight visible.
Complexitydifferent
MediumHighMediumLow
Timedifferent
30-90 min1-4 Wochen1-2 Wochen25-40 min
Participantsdifferent
1-61-61-61-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListExperiment results, Decision log, Learning summaryExperiment card, Result summary, Next betLearning Card with evidence and next action
Tagsno overlap
DecisionTreeOptions
ExperimentsGrowthAnalyticsValidation
MarketingGrowthExperimentsLearning
ExperimentsValidationDiscoveryLearning
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