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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
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.
Complexitydifferent
MediumLowHighLow
Timedifferent
30-90 min30-60 min1-4 Wochen1-5 Tage
Participantsdifferent
1-63-101-6Nutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Decision Tree, Option Map, Assumption ListRisk Matrix, Top Risk ListExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
DecisionTreeOptions
RiskDecisionPrioritizationAssessment
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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