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Criterion
Paper illustration for Flywheel.
Growth
Flywheel
Paper illustration of RAID Log with a method-specific labelled workspace.
Delivery
RAID Log
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
A/B Testing workspace showing the question, observations, and next decision.
Growth
A/B Testing
Purposedifferent
Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth.Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as a RAID Log and a source for status reporting.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.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
MediumLowLowHigh
Timedifferent
60-120 min30 min Setup, dann laufend30-60 min1-4 Wochen
Participantsdifferent
3-81-3 maintaining, briefing for everyone1-51-6
Formatdifferent
WorkshopAsyncWorkshop + asyncAsync
Outputdifferent
Flywheel Map, Friction Points, Growth Levers, Experiment BacklogRAID Log, Status Report SourceCompleted Experiment Canvas, Success MetricExperiment results, Decision log, Learning summary
Tagsno overlap
GrowthRetentionConversion
RiskTrackingStakeholdersGovernance
ExperimentsValidationDiscoveryHypothesis
ExperimentsGrowthAnalyticsValidation
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