CrUX History.

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CrUX historical Core Web Vitals report for your page

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CrUX History




Largest Contentful Paint
--
stable

LCP distribution

0
25
50
75
100

LCP scores (75th percentile)

0
25
50
75
100
0
25
50
75
100
dec
march
april
Interaction to Next Paint
--
stable

INP distribution

0
25
50
75
100

INP scores (75th percentile)

0
25
50
75
100
dec
march
april
Cumulative layout shift
--
stable

CLS distribution

0
25
50
75
100

CLS scores (75th percentile)

0
25
50
75
100
dec
march
april
First Contentful Paint
--
stable

FCP distribution

0
25
50
75
100

FCP scores (75th percentile)

0
25
50
75
100
dec
march
april
First Input Delay
--
stable

FID distribution

0
25
50
75
100

FID scores (75th percentile)

0
25
50
75
100
dec
march
april
Time to First Byte
--
stable

TTFB distribution

0
25
50
75
100

TTFB scores (75th percentile)

0
25
50
75
100
dec
march
april

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Unveiling the Power of CRUX History API: A Leap Forward in Web Browsing

Introduction:

In the ever-evolving landscape of web development, the need for more robust and efficient tools to understand user behavior and optimize online experiences is paramount. Google, at the forefront of innovation, has introduced the CRUX (Chrome User Experience) History API, a groundbreaking technology that provides developers with unprecedented access to detailed user browsing data. In this article, we will explore the CRUX History API, its evolution, and the myriad possibilities it unlocks for web developers.

Understanding CRUX:

CRUX, initially introduced as the Chrome User Experience Report, is a public dataset powered by real user performance data from Chrome users around the world. This data is aggregated and anonymized, offering insights into key metrics such as page load times, interactivity, and visual stability. The CRUX History API builds upon this foundation, allowing developers to access historical user experience data and gain deeper insights into their websites' performance over time.

Evolution of CRUX History API:

The CRUX History API represents a significant evolution from the static snapshots provided by the Chrome User Experience Report. With this API, developers can access a time-series of metrics, enabling them to analyze trends, identify performance bottlenecks, and make informed decisions to enhance user experiences. This dynamic approach allows for a more comprehensive understanding of how a website's performance evolves under different conditions.

Key Features and Capabilities:

  • Time-Series Data: The CRUX History API provides access to a wealth of time-series data, allowing developers to track changes in performance metrics over days, weeks, or months. This granular information is invaluable for identifying patterns, diagnosing issues, and implementing targeted improvements.
  • Customizable Metrics: Developers can choose from a range of performance metrics, including but not limited to First Contentful Paint (FCP), Largest Contentful Paint (LCP), and Cumulative Layout Shift (CLS). This flexibility empowers developers to focus on the metrics most relevant to their specific optimization goals.
  • Segmentation: CRUX History API supports data segmentation based on various dimensions, such as device type, network conditions, and geographical location. This enables developers to understand how different user segments experience their websites and tailor optimizations accordingly.
  • Integration with Existing Tools: The API seamlessly integrates with popular performance monitoring and analytics tools, facilitating a streamlined workflow for developers who are already using tools like Lighthouse, PageSpeed Insights, and others.

Use Cases:

  • Performance Trend Analysis: By leveraging the CRUX History API, developers can conduct in-depth analyses of performance trends over time, helping them understand the impact of changes, updates, or optimizations on user experience.
  • Proactive Issue Identification: Continuous monitoring using the API allows developers to identify and address performance issues before they escalate. This proactive approach ensures a consistently smooth and optimized user experience.
  • Geographical Optimization: With the ability to segment data by location, developers can optimize their websites based on the specific needs and preferences of users in different regions.
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