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Criterion
Paper illustration for Intervention Mapping.
Systems Thinking
Intervention Mapping
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Causal Loop Diagram workspace showing the question, observations, and next decision.
Systems Thinking
Causal Loop Diagram
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Purposedifferent
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 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.A Causal Loop Diagram makes feedback, reinforcement, and balance in a system legible. It uncovers side effects and self-reinforcement that stay hidden in linear explanations.When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.
Complexitydifferent
HighHighMediumMedium
Timedifferent
1-5 Tage1-4 Wochen1-3 h45-60 min
Participantsdifferent
4-121-62-82-8
Formatdifferent
Workshop + asyncAsyncWorkshopWorkshop + async
Outputdifferent
Logic Model, Change Objectives, Intervention Components, Evaluation PlanExperiment results, Decision log, Learning summaryCausal Loop Diagram, Feedback Notes, Leverage PointsAssumption map, Test backlog, Risk ranking
Tagsno overlap
ChangeSystems thinkingCapability
ExperimentsGrowthAnalyticsValidation
FeedbackSystems thinkingCausalityDynamics
AssumptionsRiskExperimentsValidation
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