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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 Counter Metrics with its method-specific working model.
Product Strategy
Counter Metrics
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
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 a headline metric could mask side effects, it adds guardrail signals against unwanted outcomes. It connects customer value, product logic, and decision priorities. The result is captured as a counter-metric list and guardrail definitions.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.
Complexitydifferent
LowHighLowLow
Timedifferent
30–45 min1-4 Wochen30-60 min1-5 Tage
Participantsdifferent
1-101-62-6Nutzertraffic
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
HMW Questions, Challenge Framing, Idea PromptsExperiment results, Decision log, Learning summaryCounter Metric List, Guardrail DefinitionsInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
FramingOpportunityIdeationQuestions
ExperimentsGrowthAnalyticsValidation
MetricsMeasurementStrategyExperiments
ValidationExperimentsDemandGrowth
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