How Analytics Helped Solve a UX Issue
UX and analytics make a great team. Your website analytics can give you insights enabling you to learn about your users, track their journeys, and find potential problem areas. You can use the quantitative data to inform your qualitative UX approach. Remember, your analytics tell you what’s happening on your website, while UX techniques such as usability testing will help uncover why things are happening.
There are various ways that Google Analytics can be used to uncover how your users are navigating your website. Within the Pages report you can drill down to see how users are navigating to, and from, a selected page in your website. But the User Flow and Behavior Flow reports give more information on multi-step journeys from your most popular landing pages onwards.
These reports can be hard to analyze, particularly for large websites, due to the fact that there are unlikely to be a series of clear pathways through your website. You’ll find that there are huge numbers of paths that different users can take, which makes finding insights from these reports quite challenging. However, they can be useful for getting a good top-level overview and showing the most dominant pathways through a site. While they suffer from grouping multiple pages, you can often get a good idea of the most common journeys taken by users.
One example of how I’ve used these reports in the past to inform my UX work has been looking out for pogo sticking.
Pogo sticking describes where users bounce between two pages on a website instead of progressing their journey through the site. It can be a sign of confusion on the users’ part and is unlikely to help you convert those users.
The Nielson/Norman group wrote this guide to pogo sticking, which explains it in more detail. It covers some possible reasons behind pogo sticking behavior, and also gives some potential solutions to these problems.
A Pogo Sticking Case Study
A client of mine ran a travel website offering bespoke holidays based a variety of activities and locations. They believed there were opportunities to improve their conversion rate, and I started looking for those opportunities within their analytics.
One big issue became apparent when I first looked at their behavior flow reports. As the simplified diagram below shows, there was a clear case of pogo sticking between the home page and the search results page.
As seen below, there are lots of users landing on the home page before going on to the search results page as their next step. The problem is that the next step for a lot of these users is to return to the home page rather than move on to other pages.
The home page placed search front and center, so it was no surprise that the search results pages were the most popular destination from the home page. However, it was a surprise to note the pogo sticking, as this suggested that users were not seeing the search results they expected. Looking in more detail at the home page, we noticed a potential issue. The search functionality allowed users to search by activity or location, but the way the boxes were laid out on the home page made it look like users were able to search by location and activity.
This meant that users thought they were searching for specific activities within a destination but were then presented with search results showing all activities at a destination.
We ran some usability testing sessions on the website and these showed, as expected, that there was confusion over the search functionality. During the testing sessions, users would attempt to search by location and activity without realizing that the option was not available. This led to unexpected search results and users returning to the home page to attempt their search again. Seeing individual users displaying the same pogo sticking behavior as that demonstrated in Google Analytics enabled us to dig deeper into why this issue was occurring.
The client didn’t have the development resources available to make major changes to how the search functionality worked, so we couldn’t suggest large-scale changes. Instead, we set about finding a design to minimize the pogo sticking by simplifying the search functionality and making it clear to users that they could search by destination or activity.
After sketching out and discussing various solutions, it was decided that introducing tabs was the best approach — to ensure it was clear that there were two separate search options available. This meant that users were able to choose between “activity” or “location” searches. The following wireframe shows our initial design.
This design required minimal development and was aimed specifically at tackling the pogo sticking issue.
This design was implemented on the home page and saw an immediate reduction in pogo sticking between the home page and search pages. This, in turn, led to more users getting to view destination and activity pages and also led to an overall increase in conversions. The following screenshot shows that pogo sticking was still an issue, but that there was a notable reduction in this type of behavior.
The longer-term plan is to further improve the search functionality by adding in a level of faceted search — allowing users to filter their search results and find the right destinations and activities for their requirements. This will reduce the pogo sticking even further and lead to a much more efficient way to find the right holiday.
Other Ways to Use Analytics to Inform Your UX
We’ve looked at one example of how analytics data can be used to identify a particular issue with the user journey. There are lots of other ways analytics can be used to help inform your UX decisions.
Starting off your UX work by looking at your website analytics for potential issues is a great way to find problems you might not have even been aware of. Website analytics are often overlooked during the UX process, but your analytics can be used to:
- analyze key user journeys
- identify potential problem areas on your website
- find out more about your website users
- measure the impact of your design changes
- create reports to show the value of your UX work
Taking an analytics-first approach to your UX work is great, low-cost way to start your initial UX investigative forays. Website analytics tools like Google Analytics can be free to use and you can pick up some key insights very quickly from them.
To find out more about taking an analytics-first approach to your UX work, check out my book Researching UX: Analytics.