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| Criterion |  Growth Growth Experiment |  Architecture Architecture Decision Record |  Architecture C4 Model |  Growth A/B Testing |
|---|---|---|---|---|
Purposedifferent | 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. | An ADR permanently records an architecture decision with context, trade-offs, and consequence. It creates continuity for later changes because the decision path stays traceable. | The C4 Model makes a system legible across several resolution levels, from context down to code. It suits situations where different audiences need to understand the same architecture from different altitudes. | 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 | Low | Low | High |
Timedifferent | 1-2 Wochen | 15-45 min | 1-4 h | 1-4 Wochen |
Participantsdifferent | 1-6 | 1-3 | 1-5 | 1-6 |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Experiment card, Result summary, Next bet | ADR File, Decision Log, Rationale | Context Diagram, Container Diagram, Component Diagram | Experiment results, Decision log, Learning summary |
Tagsno overlap | MarketingGrowthExperimentsLearning | ArchitectureRationaleDocumentationGovernance | ArchitectureCommunicationVisualization | ExperimentsGrowthAnalyticsValidation |