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Criterion
How Might We
Innovation
How Might We
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
With a stuck problem carrying many implicit assumptions, the method translates observations into open, workable questions. It sharpens the problem frame without pre-thinking the solution, turning frustration or fuzziness into a search space with clear direction.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 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.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
LowHighMediumLow
Timedifferent
30–45 min1-4 Wochen1-5 Tage30-60 min
Participantsdifferent
1-101-6Nutzertraffic1-5
Formatdifferent
Workshop + asyncAsyncAsyncWorkshop + async
Outputdifferent
HMW Questions, Challenge Framing, Idea PromptsExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning DecisionCompleted Experiment Canvas, Success Metric
Tagsno overlap
FramingOpportunityIdeationQuestions
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
ExperimentsValidationDiscoveryHypothesis
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