If you use Google Analytics to explore traffic and user trends on your website, then you’ve probably come across the term “bounce rate.” Google defines bounce rate as the percentage of single-page visits to your site. In other words, when a person lands on your site and then leaves again without ever going beyond the entrance page, it counts toward your bounce rate.
Google Analytics uses bounce rate to determine how relevant your landing page is to visitors. A high bounce rate indicates that whatever search terms brought users to your page are not relevant to your site. Google will not directly lower your search engine results page (SERP) rank for those search terms, but it is an indicator that something may be wrong with the content on your page. This, obviously, is bad for your website because it will eventually lead to a lowering of your rank. Unfortunately, bounce rate isn’t a perfectly clear term and so it can be difficult to make the appropriate adjustments to your site based on bounce rate if you don’t take care to properly set up Google Analytics. Here is a look at what bounce rate really means and how you can fix it.
Bounce Rate Defined
On its surface, bounce rate appears straightforward. After all, the formula for calculating bounce rate is simple division where the total number of visits to just one page are divided by the total number of visits to the site (written as Rb = Tv/Te, where Rb is bounce rate, Tv is total page visits, and Te is total entries to site). The trouble with this definition of bounce rate is that it’s wrong. It’s wrong despite the fact that it comes directly from the Google Analytics Help Center.
Bounce rate is actually calculated using “engagement hits.” Engagement hits are pageviews, events, eCommerce clicks, eCommerce transactions, social media shares, and so forth. What this means is that a social media share is counted as a hit for purposes of calculating bounce rate. This can tank your bounce rate though because every event is measured as leaving the site. Let’s say, for instance, that a person comes to your site and enjoys the page. He “likes” that page through a Facebook link. If you haven’t properly constructed that link, Google Analytics will read that “like” as a bounce because it thinks the user has left the page after a single hit. Fortunately, there are ways to deal with this issue and others that artificially lower bounce rate.
To ensure that social media shares, eCommerce clicks, and so forth don’t count as bounces, you need to make sure that those events have been set to “non-interaction.” Google Analytics provides a non-interaction parameter in its _trackEvent() method that allows you to count the event as an event and not a bounce. You need to set this property appropriately so that Google doesn’t think people are leaving your page every time they click on a social media share link.
You may think that this is a minor problem, but it isn’t. To demonstrate just how big of a problem it is, consider that even clicking the “next” button on a photo slider could be counted as an event and a bounce. With the non-interaction setting enabled, the “next” button click is counted only as an event and has no impact on bounce. The result is that your bounce rate actually indicates pageviews, which is what you want, rather than events. This means that you can finally start to determine how relevant your content is.
How Google Uses Bounce Rate
Google doesn’t use bounce rate to directly calculate PageRank. The company doesn’t directly use bounce rate from Google Analytics for the simple reason that it isn’t reliable. Google does, however, use on-page time and other metrics to determine bounce rate and thus PageRank. The reason you need to worry about bounce rate, however, is that it is a good metric for determining the relevancy of your pages to users and thus for getting an estimate of how Google is going to rank that page. If you have set it up correctly, with the non-interaction property for events that don’t take users away from the page, then Google Analytics will give you great results that you can use to improve your website.
The Limits of Bounce Rate
You shouldn’t rely too much on bounce rate if your site is primarily a content site that offers news, blog posts, or relatively unrelated content. The reason you should be wary of bounce rate in these settings is that people will often read an entire article or blog entry and then leave. Bounce rate doesn’t reflect the fact that they spent loads of time reading an entry and stayed on the page for a long time. Only an analysis of session time will tell you that.
Another thing that bounce rate doesn’t reflect is how often people return to your site. Your content may be highly relevant, but users may only read a page at a time before leaving. The fact that they return again and again, however, isn’t captured by bounce rate. Obviously, if users keep coming back, you are doing something right.
Fortunately, many factors can be tracked in Google Analytics to help you determine the relevancy of your content. Session time can be tracked, for instance, to determine how long people stay on a particular page. You can also track unique visitors, frequency, and “recency” metrics to determine how many new people come to your page, own often people return, and how soon people return. You can even track scroll rate to see how fast people are moving through content.
Getting Google Analytics Right
Getting Google Analytics to properly measure the metrics that will impact decisions about content, ads, and keyword use isn’t easy. You need to pay attention to how your cookies are designed and how Google Analytics is set to measure certain metrics (e.g. bounce rate, frequency, unique visitors). Unfortunately, there is no one-size-fits-all approach to setting these metrics. The only general rule, in fact, is to keep things in context.
If you understand what you are trying to measure, then it becomes easier to set Google Analytics and other analytics software to zero in on important metrics. For instance, with bounce rate, you want to measure pageviews and not events. By understanding that, you can set Google Analytics to ignore social media shares, eCommerce events, and so forth. Pay close attention to the factors that influence a metric in your analytics software to ensure that it provides useful, actionable information.