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Criterion
How Might We
Innovation
How Might We
Funnel Analysis workspace showing the question, observations, and next decision.
Growth
Funnel Analysis
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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 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 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.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
LowMediumLowHigh
Timedifferent
30–45 min1-3 h30-60 min1-4 Wochen
Participantsdifferent
1-101-51-51-6
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
HMW Questions, Challenge Framing, Idea PromptsFunnel report, Drop-off analysis, Optimization hypothesesCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summary
Tagsno overlap
FramingOpportunityIdeationQuestions
AnalyticsConversionGrowth
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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