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Criterion
Paper illustration of a calm four-quadrant Assumption Map with hypothesis cards and emphasis on important assumptions with little evidence.
Product Discovery
Assumption Mapping
Paper illustration of a branching category tree with a highlighted search path and possible dead ends.
UX Research
Tree Testing
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Purposedifferent
When assumptions still sit unordered in the room, it weighs uncertainty against leverage. It makes visible which hypotheses should be checked first.When a navigation exists but search paths still fail, tree testing checks findability without visual distraction. The method shows whether labels, levels, and paths really lead to the intended destination.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 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.
Complexitydifferent
MediumMediumHighMedium
Timedifferent
45-60 min1-2 Tage1-4 Wochen1-2 Wochen pro Iteration
Participantsdifferent
2-8Based on research question1-62-6
Formatdifferent
Workshop + asyncAsyncAsyncWorkshop + async
Outputdifferent
Assumption map, Test backlog, Risk rankingFindability Metrics, Path Analysis, Revised IAExperiment results, Decision log, Learning summaryPrioritized Assumption List, Test Plan, Results Report
Tagsno overlap
AssumptionsRiskExperimentsValidation
Information architectureNavigationFindability
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryAssumptions
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