As stated by Google, three user experience metrics are most likely to become the new search ranking factors. These metrics are visual stability, interactivity, and loading speed. Together they are known as the Core Web Vitals. Google will consider metrics like safety, security, friendliness, and lack of pop-ups as the new signals used for assessing page experience and making the final call to decide whether the page deserves to be raked.
These new metrics will not come into play until next year. However, the keener SEOs are chasing one another for getting a perfect score. For others, it is too early to worry about the Core Web Vitals, but it will not hurt if you want to learn about their importance.
What is the core Web Vitals?
Core web vitals could be thought of as the outcomes of a long search in the quest to deliver a reliable user experience. Through all these years, Google has been putting into test several metrics to measure perceived experience when it comes to interacting with the web page. There are several web design and SEO metrics, which come close, although none of them hits the bull’s eye until now.
Google has put forward that the new fusion of the three user experience metrics will finally establish itself as the determinant of the first impression that a web page casts on users. Moreover, Google has put forward that web pages, which suffices the benchmark of positive first impressions, are less likely to lose users when a page loads.
Largest Contentful Paint (LCP)
It evaluates loading performance, and it is reported through benchmarks such as Good for a load time of 2.5 seconds and poor for a load time of 4 seconds or more. Google will use this metric to ascertain the look and feel of a page. BeforeLCP, there were metrics like First CPU Idle, Time to Interactive, First Meaningful Paint, First Contentful Paint, and First Paint. All of these had their limitations. Although LCP is far from being perfect, it is currently the best metric.
The calculation of LCP is done by timing the loading of the largest content element, i.e., video, image, text. Google keeps hopping to the new largest element as the screen composition keeps changing. It continues to do so until the page is fully loaded or the user starts interacting with the page. One needs to understand that there are several components, which can affect the loading speed.
First Input Delay
It evaluates the responsiveness of a page, and it is reported through the following benchmarks like Good for 100 ms and Poor for 300 ms or more. You can think of FID as the time taken by a web page when it comes to reacting to the first action. The measurement of FID can be done only when the site is live, and it requires an actual user when it comes down to the choice of performing the first action. IN simulated conditions like the ones available in labs, FID is substituted by TBT, i.e., Total Blocking Time. It refers to the period when the first content appears, and the page becomes responsive. It is something that is correlating with FID but reports larger values.
Cumulative Layout Shift
Cumulative Layout Shift is concerned with the evaluation of visual stability. It is reported with benchmarks like Layout shift, i.e., content jank or layout jank. You can think of it as something where the content keeps moving even though the page appears to be fully loaded. It can sometimes be more than annoying, compelling you to click on the wrong thing, thereby provoking unwanted changes in a page.
The calculation of CLS is done by multiplying the screen share that shifted suddenly while loading with the distance traveled. CLS optimization is the easiest among all the core vitals. It comes down to the inclusion of size attribute for your videos and images while inserting new content over existing content.
Where can you find core web vitals?
You can measure the vitals with the help of these six tools for web developers like Page Speed Insights, Search Console, Chrome UX Report, Chrome DevTools, Lighthouse, and Web Vitals Chrome Extension. There is a point of distinction between these tools; some will use field data from actual users, while others will measure performance by simulating user behavior in a lab environment.
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