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Criterion
Paper illustration of Shape-first Modeling with its method-specific working model.
Knowledge Modeling
Shape-First Modeling
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of a Test Card with four fields for hypothesis, test, metric, and success threshold.
Product Discovery
Test Card
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
Shape-First Modeling defines data quality through shapes before implementation or integration frays at the edges. The approach fits when validation and data contracts should be part of the design from the start.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.The Test Card turns a critical assumption into a testable claim and specifies in advance which result counts as success.When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric.
Complexitydifferent
MediumHighLowLow
Timedifferent
Halber Tag pro Domain Slice1-4 Wochen20-35 min30-60 min
Participantsdifferent
1-41-61-51-5
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
SHACL or ShEx Shapes, Validation Reports, Data Contracts, Shape DocumentationExperiment results, Decision log, Learning summaryTest Card with a pre-set thresholdCompleted Experiment Canvas, Success Metric
Tags1 shared
Knowledge graphValidationSemantic
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
ExperimentsValidationDiscoveryHypothesis
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