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Criterion
Paper illustration of GIST Planning with its method-specific working model.
Product Strategy
GIST Planning
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
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 for Fake Door Test
Product Discovery
Fake Door Test
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 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.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.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
Wochen bis Monate je Goal1-2 h Setup, laufend1 Tag bis mehrere Wochen1-5 Tage
Participantsdifferent
3-102-64-10Nutzertraffic
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopAsync
Outputdifferent
Goals, Idea bank, Step-project list, Tasks, Learning reportsOpportunity Solution Tree, Experiment Backlog, Learning LogProblem Statement, Prototype, Test LearningsClick Data, Interest Signal, Learning Decision
Tagsno overlap
RoadmapOutcomesPlanningExperiments
DiscoveryOutcomesExperimentsOpportunity
InnovationPrototypeResearch
ValidationExperimentsDemandDiscovery
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