Best practices for measuring Web Vitals in the field

Best practices for measuring Web Vitals in the field

It draws data from Google's new Web Vitals engine released on May 5, 2020. ... To provide a good user experience, LCP should occur within 2.5 seconds of page load. ... measurement of Core Web Vitals in both the report's lab and field sections. ... Review our Privacy Policy for more information about our privacy practices.

Having the ability to measure and report on the real-world performance of your pages is critical for diagnosing and improving performance over time. Without field data, it's impossible to know for sure whether the changes you're making to your site are actually achieving their desired results.

Many popular Real User Monitoring (RUM) analytics providers already support the Core Web Vitals metrics in their tools (as well as many other Web Vitals). If you're currently using one of these RUM analytics tools, you're in great shape to assess how well the pages on your site meet the recommended Core Web Vitals thresholds and prevent regressions in the future.

While we do recommend using an analytics tool that supports the Core Web Vitals metrics, if the analytics tool you're currently using does not support them, you don't necessarily need to switch. Almost all analytics tools offer a way to define and measure custom metrics or events, which means you can likely use your current analytics provider to measure the Core Web Vitals metrics and add them to your existing analytics reports and dashboards.

This guide discusses best practices for measuring Core Web Vitals metrics (or any custom metrics) with a third-party or in-house analytics tool. It can also serve as a guide for analytics vendors wishing to add Core Web Vitals support to their service.

Use custom metrics or events #

As mentioned above, most analytics tools let you measure custom data. If your analytics tool supports this, you should be able to measure each of the Core Web Vitals metrics using this mechanism.

Measuring custom metrics or events in an analytics tool is generally a three-step process:

  1. Define or register the custom metric in your tool's admin (if required). (Note: not all analytics providers require custom metrics to be defined ahead of time.)
  2. Compute the value of the metric in your frontend JavaScript code.
  3. Send the metric value to your analytics backend, ensuring the name or ID matches what was defined in step 1 (again, if required).

For steps 1 and 3, you can refer to your analytics tool's documentation for instructions. For step 2 you can use the web-vitals JavaScript library to compute the value of each of the Core Web Vitals metrics.

The following code sample shows how easy it can be to track these metrics in code and send them to an analytics service.


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