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Last active May 21, 2021
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(10min demo at the meetup, 20 November 2019, Amsterdam)

CrUX is the Chrome User Experience Report, a public dataset of performance and UX data from real Chrome users in the field.

Quick facts:

  • Launched in November 2017
  • Monthly data dumps (second Tuesday)
  • 15,345,058 origins published since launch
  • ~6M distinct origins per month

Quick links:

What's new: Performance chapter of the Web Almanac

Using CrUX data from the field, I wrote the Performance chapter of the brand new Web Almanac. I look at FCP, TTFB, and FID experiences across all ~6M websites to try to understand how users are experiencing the web.

distribution of FCP performance

distribution of desktop and mobile FID performance

What's new: Speed Report in Search Console

Search Console

  • FCP and FID fast/moderate/slow per URL
  • URL clustering

What does CrUX have to do with Search Console? Speed is a ranking factor for mobile searches. SC is a webmaster tool for understanding how to succeed with Search.

"there is no tool that directly indicates whether a page is affected by this new ranking factor"

What's new: CLS, LCP, and TTFB

  • Time to First Byte (TTFB) powers the leaderboard of host performance.

  • Largest Contentful Paint (LCP) is a new metric to the web platform that helps developers to understand how users visually perceive page loads by reporting the time until the largest element is rendered.

  • Cumulative Layout Shift (CLS) leverages the Layout Stability API to quantify if a web page has a "jank" problem.

What's old: PSI API and CrUX Dashboard

CrUX Dashboard:

  • historical trends
  • per-origin


  • trailing 30-days
  • origin and URL
  • API

PSI is "use it or lose it". So, let's use it with a Sheets script. See it in action.

What's old: BigQuery

We have lots of nice tools, but the CrUX dataset on BigQuery is still a treasure trove of insights.

  • country datasets
  • high-resolution histograms
  • experimental metrics (LCP, CLS, FID, etc)
  • ECT and form factor (desktop/phone/tablet) dimensions

Don't be afraid to roll up your sleeves, write some SQL, and mine the dataset. We've got some sample queries to get you started in the Cookbook.

If you need help

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