The majority of the time landing page analysis is the primary focus of any web analyst when carrying out a web site review. However, little attention is given to visitor departure pages, also known as the Exit Rate.
This lack of focus is somehow understandable, especially on heavy acquisition web sites, where CMOs and Heads of Digital spend heavy budgets on biddable media and want to know which channel performs best when it comes to their KPIs. Consequently, the focus goes to landing page optimization metrics, in order to analyse visitors. It’s important that you don’t, however, ignore your visitors and what they do next.
Most of the time this happens because unlike the Bounce Rate, there isn’t a set rule for the Exit Rate. A visitor could end the visit at any moment without a meaningful reason, thus it is harder to explain. I believe that an exit rate analysis can give you a lot of important answers as to why particular visitor segments are exiting your site prematurely.
Exit Rate vs Bounce Rate
Before we move on, a small explanation about the differences between the exit rate and the bounce rate.
Bounce Rate is the percentage of single-page sessions – in other words the percentage of visitors who leave your website after viewing only one page.
Exit Rate is the percentage of visitors who left your website from a particular page, after having visited another page on your site.
This is why Landing Page Analysis in Google Analytics shows you only Bounce Rate as it is an entrance page. If you want to see the Exits from that particular page you need to refer to the All Pages analysis.
What insight can the Exit Rate give you?
Firstly, I’ve already pointed out on a previous post the importance of Exit Rate percent when running a path analysis.
Secondly – and most importantly – there are two different types of Exits: natural and unnatural.
While a high exit rate on a page that belongs to your checkout funnel is bad, there is nothing wrong if your “thank you” or “order confirmation” page has 100 percent exits as it’s normal for a visitor to end the journey once the purchase/lead generation funnel is completed.
Gaining insight into visitor departure can provide useful information that will not only affect your conversion rates but also your visitor retention metrics.
Here are the most important answers you can get by running an Exit Rate percentage analysis:
• Is page content having a direct impact on visitor conversion? (product education pages with low entrances, low exit rate and high page value for example)
• From which page of the conversion path are visitors leaving the site? (Exit Rate on different funnel stages, including product pages)
• If there are exits on key product pages, then what is causing your visitors to exit? You could have both positive and negative exits 0n the same page, some people are simply researching and not ready to purchase.
• Is there a particular channel or device that causes your visitor to leave your site early?
• Are different type of visitors exiting the site from different pages?
I will give you examples for most of the above in just a moment. Before that, I want to discuss a bit the importance of customer journey mapping – not only for Exit Rate but for web analytics in general.
The importance of customer journey mapping when adding context to an “exit”
In order to answer all the above questions, you will need to map down all your user stories and define what is a natural and what is an unnatural exit.
Here is a case study example: Let us assume that we have a client who is an estate agent running various marketing campaigns in order to get traffic to the site. The web site has a property detail pages, property category pages, an availability page and form to submit your inquiry. The goal here is for people to submit their interest on a particular property via a lead generation form.
The user story here is that “A user comes to the site in order to learn more about a property, and request a call back via a lead generation form“.
Your customer journey should look something like the graph below:
Let’s do a breakdown of what we see:
- Users will visit your site from different traffic sources
- They will come to see a specific property and submit a lead form
- They will find a particular property and check availability
- A percentage of those people will start filling a lead form in order to submit their interest (submit website form)
- A percentage of those people will hit “send” and complete the journey (form received)
Unnatural Exits
- Exit rate (Drop-Off) can happen to any of your property category pages whether they landed directly or came through an internal navigation/search. People who will visit say the “flats to buy” category page are expected to choose the size of flat or their budget range and drill down the properties, not leave the site before seeing a page.
- Submit a web site “form” (with dashes) is showing that a user started submitting your form but never completed (not received). Here in reality you will not see an exit unless you implement event tracking or a heat-map tool. If you don’t have the budget for the latter, then I suggest you work on an event tracking solution that will show you which fields under-perform for further optimization. You can read an excellent article in how to Track Form abandonment with Google Tag Manager by Simo Ahava.
Natural Exits
- The page with your Thank you form received can have up to 100 percent Exit Rate, as it is normal for a user to end the visit after a inquiry form is submitted.
- A page with property description details. Properties are not like buying a CD or Groceries. It is a high-involvement product that needs a lot of thinking and has different factors that will affect the final decision. However, you should have some micro-conversion points (alert signup, subscription to newsletter, request a brochure) in order to be able to segment your audience better and breakdown exit on details page further.
Makes sense?
Important: Please bear in mind that this is one of your many user stories. You will need to map down as many as possible before jumping into conclusions. For example, you might have repeat visits that comes to the site simply to check availability. In this case, high Exit Rate is expected and normal.
This is why you need to make sure that you segment your data in a way that makes perfect sense to you, your business and your target audience.
Exit Rate Segmentation
Now that you identified your unnatural exits, the first thing you need to do is start your standard segmentation in order to identify if this is an overall problem or if some particular channels, devices or even type of users behave differently.
Let me tell you straight off the bat that it will be impossible to map down all possible scenarios so be very careful how you define success and failure.
Segment Exit Rate by Device
Next question we are trying to answer is if there is a particular device that causes your visitor to leave your site prematurely. Once you have identify your destination pages, use “Device Category” as a secondary Dimension. Your Google Analytics data should look like the table below:
We can see that Exit rate on Mobile devices is significantly up compared to desktop and tablet (also page value is very low when it comes to mobile) meaning that you need to pay attention to the experience you are offering to your mobile users. In this example, fixing user experience on mobile will increase the page value which means more conversions for you.
Segment Exit Rate by channel
In our data below, we see a key property page segmented by channel. The question we are trying to answer is “Is there a particular channel or device that causes your visitor to leave your site?“.
You notice that visitors coming via paid search are flowing nicely comparing to organic and direct traffic. You also notice the high difference in entrances between paid and organic traffic meaning that paid customers are looking for that particular page and not landing there directly. High page value also indicates that this is a page that plays an important role to your conversions.
Now that you know this, add “Paid Traffic” as your main segment and drill down to your ad groups and keywords (secondary dimension) in order to identify which keywords are bringing you leads.
You can then share your findings with your SEO department for new optimization opportunities as the performance difference is quite noticeable. You can also run the exact same analysis with Device and User Type as your secondary dimension for further information.
