Monitoring Bounce Rate and Why it Matters

Bounce rate can seem like such a silly metrics to most analysts. It can seem like it hardly ever changes day to day or vary greatly from site to site (within industries, of course). So why is it used as a key metrics in so many analytics tools? Because if analyzed correctly, bounce rate can tell you if your site is malfunctioning, if your advertising dollars are being well spent, and which channels are best at getting engaged visitors to your website.

Before we dive in, let’s make sure we are using the same definition of bounce rate, since some analytics tools calculate it differently.

Now that we’re all on the same page, let’s focus on WHY this calculation matters. If a visitor comes to your site and visits only one page and leaves, it is considered a bounce. But what if you website contains only one page? Then a bounce is ok? What we want to make sure is that we are calculating a bounce for ONLY people that came to the site and immediately left. Those are the visitors we are trying to pinpoint, and so we have to find a way to segment them away from the visitors that came to the site and had some type of interaction – for example, read your blog post, scrolled down to the bottom of the page, clicked your Facebook icon, etc.

The best way to calculate a true bounce is to add event tagging to your site that collects valuable information regarding the user’s behavior. This will be different based on your industry AND website. If feel that a user reading all the way to the bottom of a page is an engaged visitor (say you have a blog with a lot of long form content), then adding an event to collect data on scroll tracking would lower your bounce rate by taking the users that read to the bottom OUT of the bounce rate calculation. However, if your site isn’t built for much long-form engagement and you don’t think a scroll constitutes an engaged visitor, then you wouldn’t add that type of event tracking. Again, it’s very unique to your business.

There are many types of event tracking, which I will cover later, but for the extent of this post let’s assume there is proper event tracking set up to segment out true bounces from engaged single-page visitors.

Using Bounce Rate to Determine Site Malfunctions

Given the circumstances of a relatively stable bounce rate, you one day log in to your analytics tool console and see your bounce rate has gone from 40% to 20%. Is this a good thing? Did your audience become highly engaged overnight? Chances are no, they did not, but you have an errant script running on your site clogging up the data. Or, as I’ve seen happen with a previous client, the analytics tracking code was left off of the pre-screening page during an update. So the visitors that made it past that initial page were already much more likely to engage than those that already left. They collected this data for a YEAR before it was identified as a problem. Ouch.

Another cause for concern is that if your bounce rate dips below 20%. Although it seems logical to want the lowest bounce rate possible, you’ll never completely eliminate the segment of visitors that are invariably not ready to visit. This means their browser crashed, their boss walked in, they accidentally clicked on your ad (more on this later), or any other of the wide array of reasons. This segment of users will always be out there, wreaking havoc on the internet, so just get used to them.

In order to catch website issues like this in a timely manner, the best option is to set up an automated alert that triggers an email to the website administrator when the bounce rate varies by too much or drops below 20%. (For Google Analytics users: Set up these automated alerts by following these steps.)

Using Bounce Rate to Determine Good Ad Spend

For this type of analysis, I’m going to assume all of your digital ads are well-tagged with at least the following parameters:

  • Campaign
  • Medium
  • Source

Now imagine you have about $250,000 of digital ad spend a month, spread across a few different ads on multiple sites. Some sites that are running your ad are demographic focused, others are content focused. For example, you are selling tennis rackets and have ads running on,, and The first two sites are content targeted, the third is audience/demographic targeted.
After a month of the ads running, you view the metrics and find this:

Source Sessions Bounce Rate
tennisworld 1,500 65%
tennispros 2,500 98%
activepeople 800 75%

You clearly have an unengaged audience coming from And based on the monthly budget and apparent clicks, a lot of money is being spent on this ad group. Perhaps it’s not the right consumer, perhaps it’s not the right message, or perhaps it’s not the right place in the purchase funnel. Whatever the reason, the ads aren’t working on that website and someone needs to do more research as to why. In the meantime the money would be better spent somewhere else.

Using Bounce Rate to Determine the Best Ad Channels

As mentioned above, I’m going to continue to assume all your marketing efforts are properly tagged.
Now let’s imagine you are running a full-on digital assault on the millennial market, targeting through all social channels, emails, video ads, and display ads. After a month you view the results and find the following:

Medium Sessions Bounce Rate
Social 7,500 75%
Email 6,500 55%
Video Ads 3,000 80%
Display Ads 3,000 90%

You should see where I’m going from here. The display ad budget could be reallocated into the social or video ads to get a better engaged audience to the site.

So bounce rate isn’t such a meaningless number after all. It can be a proverbial canary in a coal mine for many things, including website coding issues, poor ad performance, and marketing channels. By using bounce rate as a preliminary diagnostic of digital activity, you can take your analytics to a whole new level.

Happy analyzing!

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