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Criterion
Paper illustration for Smoke Test.
Product Discovery
Smoke Test
Design Thinking as a learning loop: an observation notebook, a focused problem statement, different idea sketches, a cardboard prototype and user-test notes. Feedback leads to new understanding.
Innovation
Design Thinking
Paper illustration of Outcome-Driven Innovation with its method-specific working model.
Product Discovery
Outcome-Driven Innovation
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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.For complex user problems with an uncertain cause, the method connects observation, interpretation, and experiment into a learning cycle. It keeps the focus on real needs and avoids premature solution language. This produces robust decisions for product and service.Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs.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
LowHighHighHigh
Timedifferent
1-5 Tage1 Tag bis mehrere WochenMehrere Wochen1-4 Wochen
Participantsdifferent
Nutzertraffic4-102-6 researchers plus sample1-6
Formatdifferent
AsyncWorkshopWorkshop + asyncAsync
Outputdifferent
Interest Metrics, Conversion Signal, Learning NoteProblem Statement, Prototype, Test LearningsDesired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypothesesExperiment results, Decision log, Learning summary
Tagsno overlap
ValidationExperimentsDemandGrowth
InnovationPrototypeResearch
OutcomesInnovationResearchQuantitative
ExperimentsGrowthAnalyticsValidation
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