Logic tells us that a high bounce rate is bad and a low bounce rate is good. But that’s not always the case. A very low - single digit, or 0% - bounce rate could indicate that there is an issue with your tracking.
Of course, it’s possible that your website or landing page is so well optimised that all of your users interact and stay on site. And if that’s the case, please come into the office and tell us how you did it!
But, every time we’ve encountered a close to 0% bounce rate, it’s been caused by an error in the Google Analytics implementation.
What is a Bounce and Bounce Rate?
Google defines a bounce as ‘a session that triggers only a single request to the analytics server.’ The most common type of server request would be a pageview.
So, if a user navigates from your homepage to a product page, two requests are sent to the analytics servers and therefore a bounce does not occur.
Similarly, bounce rate is ‘the percentage of all sessions on your site in which users viewed only a single page and triggered only a single request to the analytics server.’
Context is Key
Before we look at possible reasons for a low bounce rate, it’s worth remembering that a high bounce rate can also be totally normal.
If a user enters and exits your website on the same page without visiting any other pages, it’s best to consider the context of their visit.
For instance, if a visitor needs to find your opening times or your phone number, they will likely search ‘Company X opening times’. If your website is well optimised, the first page they land on would contain that information - your contact page perhaps. Therefore, when the visitor enters the website on that page, the purpose of their visit has been achieved without the need to visit any other pages.
In this scenario, a high bounce rate demonstrates how well optimised your site is, rather than suggesting an issue. When looking at bounce rates, high or low, context is key.
Why Is My Analytics Showing a Low Bounce Rate?
Clearly, bounce rate isn’t always what it seems. And if your analytics dashboard is displaying a particularly low bounce rate it’s prudent to investigate the reason rather than sit back and feel pleased with yourself.
To help you root out potential issues with your analytics set-up, here are three things to look out for in analytics that might be giving you a lower than expected bounce rate.
1. Event Tracking Fires Automatically
After ‘pageviews’, ‘events’ are the most common types of server requests. Events are user interactions with content that can be tracked independently from a web page or a screen load. Clicks to a button, video plays and scroll tracking are all things that you can track using events.
There are two primary ways to fire an event. The first is on-click, such as when a user clicks an ‘add to basket’ button or clicks a CTA on a homepage. The second is on-load, such as when you scroll down a page or measure page load manually.
An on-click event involves the user interacting with website content, whereas an on-load event does not. As a result, we would say that an on-click event should prevent a bounce from occurring, but an on-load event should not.
When setting an on-load event, you need to set it as a ‘non-interaction’ event. This means that it won’t be counted as an interaction and your bounce rate will not be affected. When adding events using Google Tag Manager, the default is for the event to count towards the bounce, making it is easy to overlook.
2. Multiple Analytics Tags
If you have the same analytics tag added twice to a page, they will both send pageviews at the same time and in doing so create a non-bouncer. We regularly see multiple analytics tags when Google Tag Manager has recently been added to a website and has been used to deploy the Google Analytics tag, while the hardcoded tag hasn’t been removed.
Unlike the event tracking issue, this one is much easier to detect as you will be able to see an error in Google Tag Assistant (a useful plugin for Chrome which helps troubleshoot installations of various Google tags).
Within Tag Assistant, tags are colour coded based on their status. Below is a screengrab from a website that has two analytics tags. The analytics tag is coloured yellow to indicate there is an issue and Google has identified the issue as being that the same web property ID is being tracked twice.
The solution in this scenario is to remove one of the two GA tags.
Iframes are often a tracking nightmare as they are essentially a page within a page. If your webpage loads along with its Google Analytics tag and that page contains an iframe which also contains a Google Analytics tag, you are going to encounter a scenario very similar to the previous issue.
However, when your Google Analytics tag loads within an iframe, it will also send two pageviews (one for the page and one for the iframe), which means that your pages per session count will also be incorrect.
To avoid this happening, you should avoid having a Google Analytics tag that fires within an iframe. This is easily achievable if you are using Google Tag Manager to deploy Google Analytics as you can simply amend the triggers which fire the tags.
A low bounce rate is not always a good thing. If you are seeing a site-wide bounce rate of under 20%, it may warrant further investigation. You should start by looking at landing page report within Google Analytics (found under Behavior > Site Content > Landing Pages) and look at which pages have a particularly high or low bounce rate.
You may find that the three issues detailed above will only be occurring on certain web pages, rather than site-wide. In fact, the only one that we normally expect to see site-wide is the duplicated Google Analytics tag.
While a low bounce rate is often desirable, it’s all about context. If you are seeing lots of people landing on your contact page which contains your phone number, you would expect a high bounce rate as the reason for the visit can be satisfied with a single interaction.
On the flipside, a high bounce rate on your homepage could suggest you are attracting the wrong type of traffic, or your site is not well optimised.
A Word on Session Duration
As a side note, the metric Avg. Session Duration is actually a calculated metric which is calculated as Session Duration (the total length of time of all sessions) ÷ Total Sessions.
Additionally, the length of a session is calculated as the time between when the first and last interaction are sent to the analytics servers.
The reason I mention this is because, as we previously established, a bounce is a single interaction session. This means that there is no duration assigned against the session.
So, while bouncing sessions count towards the Total Sessions metric, they do not count towards the Session Duration. As a result, you will find that your Avg. Session Duration will not be accurate.
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