How Page Load Time Affects Bounce Rates

Recently, I received an email from a friend who asked a great question about bounce rates, and what exactly they mean:

We are struggling with two definitions:

1. Bounce rate refers to the people who hit one page and then leave.
2. Bounce rate may also refer to users who hit a page and then quit that page (i.e. bounce) before the page even loads.

Perhaps from an ad industry perspective, there is no difference. But we are keen to know: are people bouncing from the site because they are only viewing one page and then leaving, they are quitting the site because the darn page doesn’t even load.

Is there a way in [analytics platform] to distinguish between these two types of bounces?

As it turns out, the answer is that bounce rates measured via standad analytics platforms will only highlight the first case: People who leave after viewing the content on one page.

If the page doesn’t load, or if the user bounces from a slow page load, the analytics platform won’t register the user at all.

If you’re relying only on in-page analytics, you will never know if someone came to your site and left before the page loads.

Here’s why:

Analytics platforms, like Google Analytics and Coremetrics, rely on a piece of JavaScript imbedded on the page to send information about a website visit from the visitors browser to the analytics platform. For performance and dependancy reasons, the JavaScript tracking files are typically loaded asynchronously upon page load.

Analytics loading analysis
Visitor not tracked for 6s (click image for full report)


In simple terms:

Website analytics measurements do not begin until after the website is loaded. People who leave your website because the page is too slow will NOT register as bounces.

True bounce rates from poor performance begin at around 400ms. If your website is slow, your bounce rates are likely much higher than the numbers your analytics platforms report.

Bounce rates are not the best way to quantify the results of a performance improvement. We typically look average pages per visit, average time on site, average order value, conversion rates, and total sales for our optimization projects.

I’d be interested to hear how others tackled this problem in the comments section.

Also, if you’re interested in learning how you can make your website faster, run your site through our free Web Performance Grader and get some quick tips.

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