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| Criterion |  Product Discovery Concierge MVP |  Growth Growth Experiment |  Growth A/B Testing |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | 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 growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment. | 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 | Medium | Medium | High | Low |
Timedifferent | 1-4 Wochen | 1-2 Wochen | 1-4 Wochen | 30-60 min |
Participantsdifferent | 3-10 Kunden | 1-6 | 1-6 | 1-5 |
Formatdifferent | Workshop + async | Workshop + async | Async | Workshop + async |
Outputdifferent | Concierge Learnings, Service Blueprint, MVP Risks | Experiment card, Result summary, Next bet | Experiment results, Decision log, Learning summary | Completed Experiment Canvas, Success Metric |
Tagsno overlap | MVPValidationServiceDiscovery | MarketingGrowthExperimentsLearning | ExperimentsGrowthAnalyticsValidation | ExperimentsValidationDiscoveryHypothesis |