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Criterion
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
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
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
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 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.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.
Complexitydifferent
MediumHighMediumLow
Timedifferent
1-3 h1-4 Wochen1-2 Wochen pro Iteration30-60 min
Participantsdifferent
1-51-62-61-5
Formatdifferent
AsyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Funnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summaryPrioritized Assumption List, Test Plan, Results ReportCompleted Experiment Canvas, Success Metric
Tagsno overlap
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryAssumptions
ExperimentsValidationDiscoveryHypothesis
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