Google uses three Core Web Vitals as ranking signals: Largest Contentful Paint (LCP) for load time, Cumulative Layout Shift (CLS) for visual stability, and Interaction to Next Paint (INP) for input responsiveness. These are the floor, not the ceiling. Supplementary metrics like server response time and page weight expose the technical root causes that CWV scores obscure. The User Timing API lets you instrument milestones specific to your own application.
Performance data comes in two forms and you need both. Synthetic tests run in controlled environments with fixed network speed, device, and location, giving you deep diagnostic reports and reproducible baselines. Real user monitoring (RUM) captures what actually happens across your visitor population, including device variance, interaction patterns, and the long tail of poor experiences that no lab test will script. The gap between the two is where most teams lose time.
The article structures optimization as three sequential steps: identify slow pages using RUM and CrUX data, diagnose root causes using synthetic reports and interaction traces, then monitor continuously to catch regressions. The diagnosis section is where the piece earns a full read. It breaks down how INP failures require RUM data to trace, how LCP element identity shifts by device, and how to isolate which scripts own the most processing time. If you are guessing at causes rather than measuring them, start here.
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