{"id":4406,"date":"2021-06-10T22:08:57","date_gmt":"2021-06-10T22:08:57","guid":{"rendered":"https:\/\/www.waterscapetech.com\/?p=4406"},"modified":"2021-06-11T00:21:06","modified_gmt":"2021-06-11T00:21:06","slug":"we-analyzed-208k-webpages-heres-what-we-learned-about-core-web-vitals-and-ux","status":"publish","type":"post","link":"https:\/\/www.waterscapetech.com\/we-analyzed-208k-webpages-heres-what-we-learned-about-core-web-vitals-and-ux","title":{"rendered":"We Analyzed 208K Webpages. Here\u2019s What We Learned About Core Web Vitals and UX"},"content":{"rendered":"
We analyzed 208,085 webpages to learn more about Core Web Vitals.<\/p>\n
First, we established benchmarks for Cumulative Layout Shift, First Input Delay, and Largest Contentful Paint.<\/p>\n
Then, we looked into the correlation between Core Web Vitals and user experience metrics (like bounce rate).<\/p>\n
Thanks to data provided by\u00a0WebCEO<\/a>, we were able to uncover some interesting findings.<\/p>\n Let\u2019s dive right into the data.<\/p>\n Here is a Summary of Our Key Findings:<\/p>\n 1.\u00a053.77% of sites had a good Largest Contentful Paint (LCP) score.<\/strong>\u00a046.23% of sites had \u201cpoor\u201d or \u201cneeds improvement\u201d LCP ratings.<\/p>\n 2.\u00a053.85% of websites in our data set had optimal First Input Delay (FID) ratings.<\/strong>\u00a0Only 8.57% of sites had a \u201cpoor\u201d FID score.<\/p>\n 3.\u00a065.13% of analyzed sites boasted good optimal Cumulative Layout Shift (CLS) scores.<\/strong><\/p>\n 4. The average LCP of the sites we analyzed clocked in at\u00a02,386 milliseconds<\/strong>.<\/p>\n 5. Average FID was\u00a0137.74 milliseconds<\/strong>.<\/p>\n 6. The mean CLS score was\u00a00.14<\/strong>. This is slightly higher than the optimal score.<\/p>\n 7. The most common issues impacting LCP were\u00a0high request counts and large transfer sizes<\/strong>.<\/p>\n 8. Large layout shifts were the #1 cause of poor CLS scores.<\/p>\n 9. The most common issue affecting FID was\u00a0an inefficient cache policy<\/strong>.<\/p>\n 10. There was\u00a0a weak correlation between Core Web Vital scores and UX metrics<\/strong>.<\/p>\n 11. We did find that\u00a0FID did tend to slightly correlate with page views<\/strong>.<\/p>\n Our first goal was to see how each site performed based on\u00a0the three factors that make up Google\u2019s Core Web Vitals<\/a>: Largest Contentful Paint, Cumulative Layout Shift, and First Input Delay.<\/p>\n <\/p>\n<\/div>\n Specifically, we wanted to determine the percentage of pages that were classified as \u201cgood\u201d, \u201cneeds improvement\u201d and \u201cpoor\u201d inside of each site\u2019s Search Console.<\/p>\n To do this, we analyzed anonymized Google Search Console data from 208k pages (approximately 20k total sites).<\/p>\n Our first task: analyze\u00a0LCP (Large Contentful Paint)<\/a>. In simple terms, LCP measures how long it takes a page to load its visible content.<\/p>\n Here\u2019s how the sites that we analyzed fared:<\/p>\n As you can see, the majority of sites that we looked at had a \u201cgood\u201d LCP rating. This was higher than expected, especially when taking into account other benchmarking efforts (like\u00a0this one by iProspect<\/a>).<\/p>\n It may be that the websites in our dataset are especially diligent about page performance. Or it may be partly due to a sample size difference (the iProspect analysis continuously monitors 1,500 sites. We analyzed 20,000+).<\/p>\n Either way, it\u2019s encouraging to see that only about half of all websites need to work on their LCP.<\/p>\n Next, we looked at Search Console reported\u00a0First Input Delay (FID)<\/a>\u00a0ratings. As the name suggests, FIP measures the delay between the first request and a user being able to input something (like typing in a username).<\/p>\n Here\u2019s a breakdown of FID scores from our dataset:<\/p>\n Again, just over half of the sites we looked at had \u201cgood\u201d FID ratings.<\/p>\n Interestingly, very few (8.57%) had \u201cpoor\u201d scores. This shows that a relatively small number of sites are likely to be negatively affected once Google incorporates FID into their algorithm.<\/p>\n53.77% of Websites Had an Optimal Largest Contentful Paint Score<\/h2>\n
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53.85% of Websites We Analyzed Had Good First Input Delay Ratings<\/h2>\n
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65.13% of Sites Had an Optimal Cumulative Layout Shift Score<\/h2>\n