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Criterion
Paper illustration of Shape Up with its method-specific working model.
Delivery
Shape Up
Surveys method illustration showing its working structure
UX Research
Surveys
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
Shape Up helps clarify scope, sequence, and delivery flow. It makes work boundaries and decisions explicit and captures results as pitches, bet-table decisions, and hill charts.When a topic needs to be validated broadly and many people can answer the same question, surveys gather structured feedback in a scalable form. Answers become comparable and segmentable instead of remaining merely anecdotal.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 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
MediumMediumHighLow
Timedifferent
6 Wochen Cycle + 2 Wochen Cool-Down3-14 Tage1-4 Wochen30-60 min
Participantsdifferent
2-4 pro Pitch50+1-61-5
Formatdifferent
Workshop + asyncAsyncAsyncWorkshop + async
Outputdifferent
Pitches, Bet-table decisions, Hill charts, Cooldown outcomesSurvey Results, Charts, Segment InsightsExperiment results, Decision log, Learning summaryCompleted Experiment Canvas, Success Metric
Tagsno overlap
PlanningDeliveryAutonomy
QuantitativeResearchValidation
ExperimentsGrowthAnalyticsValidation
ExperimentsValidationDiscoveryHypothesis
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