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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Intervention Mapping.
Systems Thinking
Intervention Mapping
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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.Intervention Mapping translates a need for change into a planned, evaluable program. The method connects target group, determinants, actions, and measurement into a traceable chain.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.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.
Complexitydifferent
MediumHighMediumHigh
Timedifferent
30-90 min1-5 Tage45-60 min1-4 Wochen
Participantsdifferent
1-64-122-81-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Decision Tree, Option Map, Assumption ListLogic Model, Change Objectives, Intervention Components, Evaluation PlanAssumption map, Test backlog, Risk rankingExperiment results, Decision log, Learning summary
Tagsno overlap
DecisionTreeOptions
ChangeSystems thinkingCapability
AssumptionsRiskExperimentsValidation
ExperimentsGrowthAnalyticsValidation
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