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| Criterion |  Architecture C4 Model |  Growth A/B Testing |  Product Strategy ICE Scoring |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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. | When ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | When demand only needs to be roughly verified, it tests interest with minimal effort. It measures whether people would take a next step at all. |
Complexitydifferent | Low | High | Low | Low |
Timedifferent | 1-4 h | 1-4 Wochen | 30-60 min | 1-5 Tage |
Participantsdifferent | 1-5 | 1-6 | 2-8 | Nutzertraffic |
Formatdifferent | Workshop + async | Async | Workshop + async | Async |
Outputdifferent | Context Diagram, Container Diagram, Component Diagram | Experiment results, Decision log, Learning summary | ICE Table, Top Idea List | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ArchitectureCommunicationVisualization | ExperimentsGrowthAnalyticsValidation | PrioritizationScoringGrowthDecision | ValidationExperimentsDemandGrowth |