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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 of a branching tree with an outcome at its root, customer opportunities, solution options and small experiment cards.
Product Discovery
Opportunity Solution Tree
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 discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure.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 Wochen1-2 h Setup, laufend30-60 min
Participantsdifferent
1-101-62-61-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
HMW Questions, Challenge Framing, Idea PromptsExperiment results, Decision log, Learning summaryOpportunity Solution Tree, Experiment Backlog, Learning LogCompleted Experiment Canvas, Success Metric
Tagsno overlap
FramingOpportunityIdeationQuestions
ExperimentsGrowthAnalyticsValidation
DiscoveryOutcomesExperimentsOpportunity
ExperimentsValidationDiscoveryHypothesis
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