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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 calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
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 assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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
MediumHighMediumMedium
Timedifferent
30-90 min1-4 Wochen45-60 min45-75 min
Participantsdifferent
1-61-62-82-8
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop
Outputdifferent
Decision Tree, Option Map, Assumption ListExperiment results, Decision log, Learning summaryAssumption map, Test backlog, Risk rankingTest Matrix, Test Plan
Tagsno overlap
DecisionTreeOptions
ExperimentsGrowthAnalyticsValidation
AssumptionsRiskExperimentsValidation
ExperimentsValidationDiscoveryOptions
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