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Criterion
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
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
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration for Fake Door Test
Product Discovery
Fake Door Test
Purposedifferent
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 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 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 is still unclear, it measures interest in a feature before it is built. It separates real behavior from polite agreement and deliberately keeps build effort small.
Complexitydifferent
MediumMediumHighMedium
Timedifferent
1-2 Wochen1-2 h Setup, laufend1-4 Wochen1-5 Tage
Participantsdifferent
1-62-61-6Nutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncAsync
Outputdifferent
Experiment card, Result summary, Next betOpportunity Solution Tree, Experiment Backlog, Learning LogExperiment results, Decision log, Learning summaryClick Data, Interest Signal, Learning Decision
Tags1 shared
MarketingGrowthExperimentsLearning
DiscoveryOutcomesExperimentsOpportunity
ExperimentsGrowthAnalyticsValidation
ValidationExperimentsDemandDiscovery
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