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Criterion
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Intervention Mapping.
Systems Thinking
Intervention Mapping
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Purposedifferent
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.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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.When many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.
Complexitydifferent
HighHighLowMedium
Timedifferent
1-4 Wochen1-5 Tage1-5 Tage1-3 h
Participantsdifferent
1-64-12Nutzertraffic1-5
Formatdifferent
AsyncWorkshop + asyncAsyncAsync
Outputdifferent
Experiment results, Decision log, Learning summaryLogic Model, Change Objectives, Intervention Components, Evaluation PlanInterest Metrics, Conversion Signal, Learning NoteFunnel report, Drop-off analysis, Optimization hypotheses
Tagsno overlap
ExperimentsGrowthAnalyticsValidation
ChangeSystems thinkingCapability
ValidationExperimentsDemandGrowth
AnalyticsConversionGrowth
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