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| Criterion |  Growth A/B Testing |  Architecture ARID (Active Reviews for Intermediate Designs) |  Growth North Star Metric |  Product Discovery Smoke Test |
|---|---|---|---|---|
Purposedifferent | 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. | ARID examines how well developers can work with a technical design. It focuses on a part of the system that can still be revised, between the architecture overview and the detailed specification. | When product teams track many metrics, the view of the actual customer outcome easily gets lost. A North Star Metric bundles growth, usage, and value contribution into one signal that makes the system's direction visible. | 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 | High | Medium | Medium | Low |
Timedifferent | 1-4 Wochen | 2–4 h review as a planning range; preparation and evaluation additional | 1-2 h | 1-5 Tage |
Participantsdifferent | 1-6 | Designers, developers as users, and facilitation | 3-8 | Nutzertraffic |
Formatdifferent | Async | Workshop + async | Workshop + async | Async |
Outputdifferent | Experiment results, Decision log, Learning summary | Prioritized development tasks, Jointly produced code or pseudocode, Observed difficulties and open design questions, Proposed design revisions | North Star metric, Input metric tree, Measurement cadence | Interest Metrics, Conversion Signal, Learning Note |
Tagsno overlap | ExperimentsGrowthAnalyticsValidation | ArchitectureEngineeringFeedbackValidationTasks | GrowthMetricsAlignmentRetention | ValidationExperimentsDemandGrowth |