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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
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
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 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 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
LowMediumHighLow
Timedifferent
30–45 min1-3 h1-4 Wochen1-5 Tage
Participantsdifferent
1-101-51-6Nutzertraffic
Formatdifferent
Workshop + asyncAsyncAsyncAsync
Outputdifferent
HMW Questions, Challenge Framing, Idea PromptsFunnel report, Drop-off analysis, Optimization hypothesesExperiment results, Decision log, Learning summaryInterest Metrics, Conversion Signal, Learning Note
Tagsno overlap
FramingOpportunityIdeationQuestions
AnalyticsConversionGrowth
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandGrowth
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