Digital marketing is a rapidly growing field where technological solutions regularly appear in response to increasing marketing needs.
Though web analytics tools (Google Analytics, Adobe Analytics…) have become mainstream for marketers, UX analysis tools (like Heap Analytics, ContentSquare, Clicktale, Hotjar, Beampulse, SessionCam) have recently broken into the market, too.
So what are they for, and how do they complement traditional web analytics tools?
Web analytics and UX analysis tools: the perfect alliance for an optimal user experience
Falling conversion rates, lower bounce rates, increased sessions following a marketing campaign… Today, traditional web analytics tools are a simple way to identify web pages where these metrics are shifting. They are also a good way to find which areas of a site or an app are not working – or those that have the best performance.
Thanks to Google Analytics or Adobe Analytics, we can quickly discover if users are running into difficulties with a website form, for instance. Nevertheless, marketers looking to take things further and understand why a given site performs well (or poorly) will soon reach the limits of these tools’ technological capabilities. The analyst will have all the jigsaw pieces in hand, but won’t be able to complete the puzzle. Enter UX analysis tools, centre stage!
Once the strength or weakness of a given page has been established, the UX analysis tool can provide user engagement levels in order to better explain behaviour. This is called in-page analytics: understanding where on the page a user has difficulties, what their scroll is like, which functions are most skipped without clicks, etc.
In this way, UX analysis tools provide marketing analysts with more detailed metrics and visitor segmentation functions than traditional tools. Google’s In-page Analytics feature and Adobe’s Activity Map, two precursors to today’s UX analytics tools, did not take off and did not develop new functions quickly enough. Web analytics leaders opted to focus on their core business, leaving an opening that players such as ContentSquare, Clicktale, Hotjar and Beampulse have filled in Europe.
In the United States, Heap Analytics is another popular solution. Some of Heap’s most significant features are: retroactive data collection; native integration with AWS Redshift; and the ability to import data from external sources (including CRM, A/B Testing tools, eCommerce platforms etc.).
UX analysis: a new digital discipline
UX analysis tools give us illustrative metrics that we can’t get from traditional tools, including:
- Scroll rate
- Time spent on a given page area
- Click recurrence and time before first click
These metrics can help us quickly understand, for example, why users encounter difficulties with certain steps of online forms. If we know that click recurrence is higher on one form page than on others, we know why the rate of exit is higher at this step in the form.
This type of analysis, easily carried out with a UX solution, would be much more complex to conduct with a web analytics tool.
Similarly, the Sunburst report from ContentSquare is an easy way to visualize user paths – which was difficult with Google’s Behavior Flow.
A Behavior Flow report, more complicated to navigate at first glance
A Sunburst report, which helps analysts understand the most used, most optimal, and most problematic user paths
To go further, UX analysis also facilitates behaviour-based user segmentation. For example, we could isolate users that hover over quick-buy pop-ups on a product list without converting, and use this segment to analyse these users’ navigation paths and interactions with product pages.
These UX behaviour segmentation features are unique, and a major differentiator for UX analysis tools compared to web analytics solutions.
Increased flexibility in settings
For UX specialist players, and ContentSquare in particular, there are no pre-analysis settings (called tagging plan): unlike traditional web analysis tools, settings are determined and updated as the analysis is carried out. Data collection relies on the page’s HTML attributes at a given moment, and not on a pre-defined list of elements to track.
This is a big advantage for marketing analysts, as it results in more flexibility. They can continually modify settings for each analysis, and can work in iterations, revising user segments or zones for analysis based on findings from previous analyses.
A big step for test launching
Beyond web analysis tools, UX analysis tools also complement testing tools, as they can be used as prerequisites to test set-up.
UX web analysis tools are thus ideal for diagnosing reasons for dysfunction on a web page. The ideal next step is to launch a test to confirm or deny a hypothesis based on the tool results.
For example, where a UX analysis tool can prove that a given field in an online form creates difficulty for users (lower click rate on the field in question, lower-than-average click recurrence), the testing tool can examine the length of the form, deleting the problematic field and setting up two versions of the the form to be tested (see example taken from a ContentSquare form below).
Click recurrence for this field shows frustration around certain buttons, which could result in users closing the form. For example, the “city” field on this personal information form leads to user hesitation and slows down form completion, with an average click rate of 3.6.
Based on test results, we can decide whether or not to implement a new version of the form. Simply put, web analysis is a way to identify symptoms of a poorly functioning site, while a UX analysis tool can identify the cause. Testing is a way to find a cure! This proves that user experience is not about intuition… It’s about data!