In order to analyze the 208,085 webpages and to learn more about Core Web Vitals the benchmarks for Cumulative Layout Shift, First Input Delay, and Largest Contentful Paint were made use of. And then the correlation between Core Web Vitals and user experience metrics (like bounce rate) was looked into. With the data provided by WebCEO, we were able to uncover some interesting findings. The analysis of these is essential for any website development company.
Here’s A Summary of The Key Findings:
53.77% of Websites Had an Optimal Largest Contentful Paint Score
Analysis of the site performance based on the three factors that make up Google’s Core Web Vitals, namely the Largest Contentful Paint, Cumulative Layout Shift, and First Input Delay were done.
This helped to determine the percentage of pages that were classified as “good”, “needs improvement” and “poor” inside of each site’s Search Console. Analyzing anonymized Google Search Console data from 208k pages (approximately 20k total sites) had helped in this process.
LCP helps to measure how long it takes a page to load its visible content. Get in touch with our web development company in the USA to know and incorporate the strategies that best suit your website.
Here’s how the sites fared on the analysis:
- Good: 53.77%
- Needs Improvement: 28.76%
- Poor: 17.47%
The majority of sites had a “good” LCP rating, higher than expected, especially when taking into account other benchmarking efforts (like this one by iProspect).
Only with the help of pro web development services can you have a high-performing website, which can showcase this kind of whooping results.
53.85% of Websites Analyzed Had Good First Input Delay Ratings
The Search Console reported First Input Delay (FID) ratings. FIP measures the delay between the first request and a user being able to input something, like typing in a username.
Here’s a breakdown of FID scores from our dataset:
- Good: 53.85%
- Needs Improvement: 37.58%
- Poor: 8.57%
Half of the sites had “good” FID ratings in the analysis and interestingly, very few (8.57%) had “poor” scores. This indicates that a relatively small number of sites are likely to be negatively affected once Google incorporates FID into their algorithm.
Get in touch with the best web development company and get your site on top of the list.
65.13% of Sites Had an Optimal Cumulative Layout Shift Score
The Cumulative Layout Shift (CLS) ratings from Search Console is a measurement of how elements on a page move while loading. Pages that are stable through the loading process display high (good) CLS scores.
Here were the CLS ratings among the sites that we analyzed:
- Good: 65.13%
- Needs Improvement: 17.03%
- Poor: 17.84%
Amongst the three Core Web Vitals scores, CLS tended to be the least problematic. Only around 35% of the sites that were analyzed needed to work on their CLS.
Average LCP Is 2,836 Milliseconds
This was done to establish benchmarks for each Core Web Vital metric. Google has created its own set of guidelines for each Core Web Vital. For example, a “good” LCP is considered to be under 2.5 seconds. In the process of analysis, LCP scores were benchmarked for the sites.
Among the sites that we analyzed, the average LCP turned out to be 2,836 Milliseconds (2.8 seconds).
Here were the most common issues that negatively impacted LCP performance:
- High request counts and large transfer sizes (100% of pages)
- High network round-trip time (100% of pages)
- Critical request chains (98.9% of pages)
- High initial server response time (57.4% of pages)
- Images not served in next-gen format (44.6% of pages)
100% of pages had high LCP scores and this was partly due to “High request counts and large transfer sizes’ ‘. Meaning, pages that are heavy with excess code, large file sizes, or both.
We are the best amongst the top web development companies in the USA, who can help you gain through these analyses.
Average FID Is 137.4 Milliseconds
The FID scores among the pages showed that the First Input Delay was 137.4 milliseconds:
Here are the most prevalent FID-related issues that we discovered:
- Inefficient cache policy (87.4% of pages)
- Long main-thread tasks (78.4% of pages)
- Unused CSS (38.7% of pages)
- Excessive Document Object Model size (22.3% of pages)
It was noted that the caching issues tended to negatively affect FID more than any other problem. Poorly-optimized code in the form of unused JS and CSS was behind many high FID scores.
Average CLS Is .14
The analysis showed that the average CLS score was .14.
This metric specifically looked at how the content on a page “shifts”. Anything below .1 is usually rated as “good” in Search Console.
The most common issues affecting the projects’ CLS included:
- Large layout shifts (94.5% of pages)
- Render-blocking resources (86.3% of pages)
- Text is hidden during web font load (82.6% of pages)
- Not preloaded key requests (26.7% of pages)
- Improperly sized images (24.7% of pages)
Looking for a web development agency in San Francisco, that can help your website also perform similarly well? We are only a call away.
How LCP Correlates With User Behavior
How accurately Core Web Vitals represent real-life user experience is something that Google themselves highlight in their “Core Web Vitals report” documentation:
In order to analyze Core Web Vitals and their impact on UX, three UX metrics designed to represent user behavior on web pages mentioned below were looked into
- Bounce rate (% of users leaving a website’s page upon visiting it)
- Page depth per session (how many pages users see before leaving the website)
- Time on the website (how much time users spend on a website in a single session)
The study indicated that if you improve a website’s Core Web Vitals, it will positively affect UX metrics and it was clear that all three different segments (Good, Poor, and Needs Improvement) are somewhat evenly distributed on the graph.
In other words, this meant that there wasn’t any direct relationship between LCP and UX metrics.
FID Has a Slight Relationship With Page Views
Next, the potential relationship between First Input Delay and user behavior was studied. Similar to LCP, it’s logical that a poor FID would negatively impact UX metrics.
If a user needs to wait to choose from a menu or type in their password he might become frustrated and bounce. And if that experience carries across several pages, it may lead to them reducing their total page views.
It was found that a high FID tends to correlate with a low number of pages per session. The opposite was also true.
Get in touch with our web development in San Jose for the kind of ideal web development and performance-enhancing services that you were looking for.
FID and Time on Site
Overall, the only instance that showed hints of correlation is when there was a comparison made between FID to the number of pages viewed per session. When it comes to bounce rate and time on site, a website’s FID appears to have no influence on user behavior.
How CLS Impacts User Behavior
Next, the investigation was on the potential link between CLS and user activity.
A poor CLS tends to frustrate users and could therefore increase bounce rate and reduce session time. Analysis for potential relationships between CLS, bounce rate, “dwell time” and pages viewed were carried out.
Overall, no significant correlation between CLS, bounce rate, time on site, or page views were sighted.
Are you considering opting for website development in San Jose? Do call us for help.
Most of the sites that were analyzed performed relatively well and were largely ready for the Google update. It was also interesting to find that the Core Web Vitals represent metrics for a positive UX on a website that didn’t show any correlation with behavioral metrics.
We would like to hear from you. Maybe you have a query or are not sure how to start about it? Get in touch with the top website development company in the USA. Our expert team would love to help you.