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Criterion
Paper illustration of GIST Planning with its method-specific working model.
Product Strategy
GIST Planning
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
Purposedifferent
GIST Planning helps clarify target groups, value, goals, and priorities. It links customer value, product logic, and decision priorities, and captures the result as goals, an idea bank, and a step-project list.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.
Complexitydifferent
MediumMediumMediumHigh
Timedifferent
Wochen bis Monate je Goal1-2 Wochen1-2 h Setup, laufend1-4 Wochen
Participantsdifferent
3-101-62-61-6
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshop + asyncAsync
Outputdifferent
Goals, Idea bank, Step-project list, Tasks, Learning reportsExperiment card, Result summary, Next betOpportunity Solution Tree, Experiment Backlog, Learning LogExperiment results, Decision log, Learning summary
Tags1 shared
RoadmapOutcomesPlanningExperiments
MarketingGrowthExperimentsLearning
DiscoveryOutcomesExperimentsOpportunity
ExperimentsGrowthAnalyticsValidation
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