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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
Paper illustration of a Test Card with four fields for hypothesis, test, metric, and success threshold.
Product Discovery
Test Card
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
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.The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.
Complexitydifferent
MediumHighLowLow
Timedifferent
30-90 min1-4 Wochen20-35 min30-60 min
Participantsdifferent
1-61-61-51-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListExperiment results, Decision log, Learning summaryTest Card with a pre-set thresholdCompleted Experiment Canvas, Success Metric
Tagsno overlap
DecisionTreeOptions
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
ExperimentsValidationDiscoveryHypothesis
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