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| Criterion |  Growth Flywheel |  Product Discovery Concierge MVP |  Product Discovery Experiment Canvas |  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. | When an idea can first fail or grow through genuine hands-on support, it relies on manual work instead of automation. It shows whether user value holds up even under manual execution. | 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 | Medium | Medium | Low | High |
Timedifferent | 60-120 min | 1-4 Wochen | 30-60 min | 1-4 Wochen |
Participantsdifferent | 3-8 | 3-10 Kunden | 1-5 | 1-6 |
Formatdifferent | Workshop | Workshop + async | Workshop + async | Async |
Outputdifferent | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Concierge Learnings, Service Blueprint, MVP Risks | Completed Experiment Canvas, Success Metric | Experiment results, Decision log, Learning summary |
Tagsno overlap | GrowthRetentionConversion | MVPValidationServiceDiscovery | ExperimentsValidationDiscoveryHypothesis | ExperimentsGrowthAnalyticsValidation |