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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of a calibrated five-by-five risk matrix with response cards.
Decision Making
Risk Matrix
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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.When a project faces many possible disruptions, it quickly becomes unclear which risks deserve attention first. It separates options, evaluation criteria, and open risks. The result is captured as a Risk Matrix and a Top Risk List.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 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
MediumLowLowHigh
Timedifferent
30-90 min30-60 min1-5 Tage1-4 Wochen
Participantsdifferent
1-63-10Nutzertraffic1-6
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Decision Tree, Option Map, Assumption ListRisk Matrix, Top Risk ListInterest Metrics, Conversion Signal, Learning NoteExperiment results, Decision log, Learning summary
Tagsno overlap
DecisionTreeOptions
RiskDecisionPrioritizationAssessment
ValidationExperimentsDemandGrowth
ExperimentsGrowthAnalyticsValidation
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