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Criterion
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 for Smoke Test.
Product Discovery
Smoke Test
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
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 demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all.When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.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
MediumLowMediumHigh
Timedifferent
1-2 h Setup, laufend1-5 Tage1-2 Wochen1-4 Wochen
Participantsdifferent
2-6Nutzertraffic1-61-6
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncAsync
Outputdifferent
Opportunity Solution Tree, Experiment Backlog, Learning LogInterest Metrics, Conversion Signal, Learning NoteExperiment card, Result summary, Next betExperiment results, Decision log, Learning summary
Tags1 shared
DiscoveryOutcomesExperimentsOpportunity
ValidationExperimentsDemandGrowth
MarketingGrowthExperimentsLearning
ExperimentsGrowthAnalyticsValidation
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