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Criterion
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
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
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 many visitors or users drop off along the way, the reason behind the number often stays hidden. Funnel Analysis exposes these transitions and makes visible exactly where the path collapses.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
MediumMediumLowHigh
Timedifferent
1-2 Wochen pro Iteration1-3 h1-5 Tage1-4 Wochen
Participantsdifferent
2-61-5Nutzertraffic1-6
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
Prioritized Assumption List, Test Plan, Results ReportFunnel report, Drop-off analysis, Optimization hypothesesInterest Metrics, Conversion Signal, Learning NoteExperiment results, Decision log, Learning summary
Tagsno overlap
ExperimentsValidationDiscoveryAssumptions
AnalyticsConversionGrowth
ValidationExperimentsDemandGrowth
ExperimentsGrowthAnalyticsValidation
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