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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption 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 an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.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.
Complexitysame
MediumMediumMediumMedium
Timedifferent
30-90 min1-2 Wochen pro Iteration45-75 min1-5 Tage
Participantsdifferent
1-62-62-8Nutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopAsync
Outputdifferent
Decision Tree, Option Map, Assumption ListPrioritized Assumption List, Test Plan, Results ReportTest Matrix, Test PlanClick Data, Interest Signal, Learning Decision
Tagsno overlap
DecisionTreeOptions
ExperimentsValidationDiscoveryAssumptions
ExperimentsValidationDiscoveryOptions
ValidationExperimentsDemandDiscovery
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