How to use the CrUX BigQuery dataset

Rick Viscomi

The raw data of the Chrome UX Report (CrUX) is available on BigQuery, a database on Google Cloud. Using BigQuery requires a GCP project and basic knowledge of SQL.

In this guide, learn how to use BigQuery to write queries against the CrUX dataset to extract insightful results about the state of user experiences on the web:

  • Understand how the data is organized
  • Write a basic query to evaluate an origin's performance
  • Write an advanced query to track performance over time

Data organization

Start by looking at a basic query:

SELECT COUNT(DISTINCT origin) FROM `chrome-ux-report.all.202206`

To run the query, enter it into the query editor and press the "Run query" button:

Enter a simple query into editor and press Run.

There are two parts to this query:

  • SELECT COUNT(DISTINCT origin) means querying for the number of origins in the table. Roughly speaking, two URLs are part of the same origin if they have the same scheme, host, and port.

  • FROM chrome-ux-report.all.202206 specifies the address of the source table, which has three parts:

    • The Cloud project name chrome-ux-report within which all CrUX data is organized
    • The dataset all, representing data across all countries
    • The table 202206, the year and month of the data in YYYYMM format

There are also datasets for every country. For example, chrome-ux-report.country_ca.202206 represents only the user experience data originating from Canada.

Within each dataset there are tables for every month since 201710. New tables for the previous calendar month are published regularly.

The structure of the data tables (also known as the schema) contains:

  • The origin, for example origin = 'https://www.example.com', which represents the aggregate user experience distribution for all pages on that website
  • The connection speed at the time of page load, for example, effective_connection_type.name = '4G' (removed from February 2025)
  • The device type, for example form_factor.name = 'desktop'
  • The UX metrics themselves
    • first_paint (FP)