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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
Paper illustration for Fake Door Test
Product Discovery
Fake Door 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 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 several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan.When demand is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
MediumLowMediumMedium
Timedifferent
30-90 min1-5 Tage45-75 min1-5 Tage
Participantsdifferent
1-6Nutzertraffic2-8Nutzertraffic
Formatdifferent
Workshop + asyncAsyncWorkshopAsync
Outputdifferent
Decision Tree, Option Map, Assumption ListInterest Metrics, Conversion Signal, Learning NoteTest Matrix, Test PlanClick Data, Interest Signal, Learning Decision
Tagsno overlap
DecisionTreeOptions
ValidationExperimentsDemandGrowth
ExperimentsValidationDiscoveryOptions
ValidationExperimentsDemandDiscovery
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