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We analyzed 208,085 webpages to larn much astir Core Web Vitals.
First, we established benchmarks for Cumulative Layout Shift, First Input Delay, and Largest Contentful Paint.
Then, we looked into the correlation betwixt Core Web Vitals and idiosyncratic acquisition metrics (like bounce rate).
Thanks to information provided by WebCEO, we were capable to uncover immoderate absorbing findings.
Let’s dive close into the data.
Here is simply a Summary of Our Key Findings:
1. 53.77% of sites had a bully Largest Contentful Paint (LCP) score. 46.23% of sites had “poor” oregon “needs improvement” LCP ratings.
2. 53.85% of websites successful our information acceptable had optimal First Input Delay (FID) ratings. Only 8.57% of sites had a “poor” FID score.
3. 65.13% of analyzed sites boasted bully optimal Cumulative Layout Shift (CLS) scores.
4. The mean LCP of the sites we analyzed clocked successful astatine 2,386 milliseconds.
5. Average FID was 137.74 milliseconds.
6. The mean CLS people was 0.14. This is somewhat higher than the optimal score.
7. The astir communal issues impacting LCP were high petition counts and ample transportation sizes.
8. Large layout shifts were the #1 origin of mediocre CLS scores.
9. The astir communal contented affecting FID was an inefficient cache policy.
10. There was a anemic correlation betwixt Core Web Vital scores and UX metrics.
11. We did find that FID did thin to somewhat correlate with leafage views.
53.77% of Websites Had an Optimal Largest Contentful Paint Score
Our archetypal extremity was to spot however each tract performed based connected the 3 factors that marque up Google’s Core Web Vitals: Largest Contentful Paint, Cumulative Layout Shift, and First Input Delay.
Specifically, we wanted to find the percent of pages that were classified arsenic “good”, “needs improvement” and “poor” wrong of each site’s Search Console.
To bash this, we analyzed anonymized Google Search Console information from 208k pages (approximately 20k full sites).
Our archetypal task: analyse LCP (Large Contentful Paint). In elemental terms, LCP measures however agelong it takes a leafage to load its disposable content.
Here’s however the sites that we analyzed fared:
- Good: 53.77%
- Needs Improvement: 28.76%
- Poor: 17.47%
As you tin see, the bulk of sites that we looked astatine had a “good” LCP rating. This was higher than expected, particularly erstwhile taking into relationship different benchmarking efforts (like this 1 by iProspect).
It whitethorn beryllium that the websites successful our dataset are particularly diligent astir leafage performance. Or it whitethorn beryllium partially owed to a illustration size quality (the iProspect investigation continuously monitors 1,500 sites. We analyzed 20,000+).
Either way, it’s encouraging to spot that lone astir fractional of each websites request to enactment connected their LCP.
53.85% of Websites We Analyzed Had Good First Input Delay Ratings
Next, we looked astatine Search Console reported First Input Delay (FID) ratings. As the sanction suggests, FIP measures the hold betwixt the archetypal petition and a idiosyncratic being capable to input thing (like typing successful a username).
Here’s a breakdown of FID scores from our dataset:
- Good: 53.85%
- Needs Improvement: 37.58%
- Poor: 8.57%
Again, conscionable implicit fractional of the sites we looked astatine had “good” FID ratings.
Interestingly, precise fewer (8.57%) had “poor” scores. This shows that a comparatively tiny fig of sites are apt to beryllium negatively affected erstwhile Google incorporates FID into their algorithm.
65.13% of Sites Had an Optimal Cumulative Layout Shift Score
Finally, we looked astatine the Cumulative Layout Shift (CLS) ratings from Search Console.
CLS is simply a measurement of however elements connected a leafage determination portion loading. Pages that are comparatively unchangeable done the loading process person precocious (good) CLS scores.
Here were the CLS ratings among the sites that we analyzed:
- Good: 65.13%
- Needs Improvement: 17.03%
- Poor: 17.84%
Among the 3 Core Web Vitals scores, CLS tended to beryllium the slightest problematic. In fact, lone astir 35% of the sites that we analyzed request to enactment connected their CLS.
Average LCP Is 2,836 Milliseconds
Next, we wanted to found benchmarks for each Core Web Vital metric. As mentioned above, Google has created their ain acceptable of guidelines for each Core Web Vital.
(For example, a “good” LCP is considered to beryllium nether 2.5 seconds.)
However, we hadn’t seen a large-scale investigation that attempted to benchmark each Core Web Vital metric “in the wild”.
First, we benchmarked LCP scores for the sites successful our database.
Among the sites that we analyzed, the mean LCP turned retired to beryllium 2,836 Milliseconds (2.8 seconds).
Here were the astir communal issues that negatively impacted LCP performance:
- High petition counts and ample transportation sizes (100% of pages)
- High web round-trip clip (100% of pages)
- Critical petition chains (98.9% of pages)
- High archetypal server effect clip (57.4% of pages)
- Images not served successful next-gen format (44.6% of pages)
Overall, 100% of pages had precocious LCP scores astatine slightest partially owed to “High petition counts and ample transportation sizes”. In different words, pages that are dense with excess code, ample record sizes, oregon both.
This uncovering is successful enactment with different investigation that we did which recovered that ample pages tended to beryllium the culprit down astir slow-loading pages.
Average FID Is 137.4 Milliseconds
We past looked astatine FID scores among the pages successful our dataset.
Overall, the mean First Input Delay was 137.4 milliseconds:
Here are the astir prevalent FID-related issues that we discovered:
- Inefficient cache argumentation (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 absorbing to spot that caching issues tended to negatively impact FID much than immoderate different problem. And, not surprisingly, poorly-optimized codification (in the signifier of unused JS and CSS) was down galore precocious FID scores.
Average CLS Is .14
We discovered that the mean CLS people is .14.
This metric specifically looks astatine however the contented connected a leafage “shifts”.Anything beneath .1 is rated arsenic “good” successful Search Console.
The astir communal issues affecting the projects’ CLS included:
- Large layout shifts (94.5% of pages)
- Render-blocking resources (86.3% of pages)
- Text hidden during web font load (82.6% of pages)
- Not preloaded cardinal requests (26.7% of pages)
- Improperly sized images (24.7% of pages)
How LCP Correlates With User Behavior
Now that benchmarks were set, we past acceptable to find retired however accurately Core Web Vitals correspond real-life idiosyncratic experience.
In fact, this narration is thing that Google themselves item successful their “Core Web Vitals report” documentation:
To analyse Core Web Vitals and their interaction connected UX, we decided to look astatine 3 UX metrics designed to correspond idiosyncratic behaviour connected webpages:
- Bounce complaint (% of users leaving a website’s leafage upon visiting it)
- Page extent per league (how galore pages users spot earlier leaving the website)
- Time connected website (how overmuch clip users walk connected a website successful a azygous session)
Our proposal was arsenic follows: if you amended a website’s Core Web Vitals, it volition positively impact UX metrics.
In different words, a tract with “good” Core Web Vitals volition person a little bounce rate, longer sessions, and higher leafage views. Fortunately, successful summation to Search Console data, this information acceptable besides contained UX metrics from Google Analytics.
Then, we simply had to comparison each website’s Core Web Vitals against each UX metric. You tin find our results for LCP below:
LCP and Bounce Rate
LCP and Pages per Session
LCP and Time connected Site
On the 3 graphs, it was wide that each 3 antithetic segments (Good, Poor and Needs Improvement) are somewhat evenly distributed connected the graph.
In different words, determination wasn’t immoderate nonstop narration betwixt LCP and UX metrics.
FID Has a Slight Relationship With Page Views
Next, we looked astatine the imaginable narration betwixt First Input Delay and idiosyncratic behavior.
Like with LCP, it’s logical that a mediocre FID would negatively interaction UX metrics (especially bounce rate).
A idiosyncratic that needs to hold to take from a paper oregon benignant successful their password is apt to go frustrated and bounce. And if that acquisition carries crossed respective pages, it whitethorn pb to them reducing their full leafage views.
With that, here’s however FID correlated with their behavioral metrics.
FID and Bounce Rate
FID and Pages per Session
Note: We recovered that a precocious FID tends to correlate with a debased fig of pages per session. The other was besides true.
FID and Time connected Site
Overall, the lone lawsuit wherever we spot hints of correlation is erstwhile we comparison FID to the fig of pages viewed per session. When it comes to bounce complaint and clip connected site, a website’s FID appears to person nary power connected idiosyncratic behavior.
How CLS Impacts User Behavior
Next, we wanted to analyse a imaginable nexus betwixt CLS and idiosyncratic activity.
It seems logical that a mediocre CLS would frustrate users. And could truthful summation bounce complaint and trim league time.
However, we weren’t capable to find immoderate lawsuit studies oregon large-scale investigation that demonstrated that precocious CLS scores power idiosyncratic behavior. So we decided to tally an investigation that looked for imaginable relationships betwixt CLS, bounce rate, “dwell time” and pages viewed. Here’s what we found:
CLS and Bounce Rate
CLS and Pages per Session
CLS and Time connected Site
Overall, we didn’t spot immoderate important correlation betwixt CLS, bounce rate, clip connected site, oregon leafage views.
I anticipation you recovered this investigation absorbing and utile (especially with Google’s Page Experience update connected the way).
I privation to convey SEO bundle WebCEO for providing the information that made this manufacture survey possible.
Overall, it was absorbing to spot that astir of the sites that we analyzed performed comparatively well. And are mostly acceptable for the Google update. And it was absorbing to find that, portion Core Web Vitals correspond metrics for a affirmative UX connected a website, we didn’t spot immoderate correlation with behavioral metrics.
Now I’d similar to perceive from you:
What’s your main takeaway from today’s study? Or possibly you person a question astir thing from the analysis. Either way, permission a remark beneath close now.