Behavioral UX Data Analysis for Website Optimization
Behavioral UX Data Analysis is one of the 4 steps of website optimization. Learn how Behavioral UX data can be used to improve websites.
Behavioral UX Data is the WHAT IS HAPPENING data. As I mentioned in a prior article, analyzing Behavioral UX data is one of the Four Big UX Optimization Steps. Because this data is quantitative in nature, it is used to identify what behaviors are, or are not, occurring on your website. This information is critical to any analysis of website optimization opportunities.
We use behavioral data to determine what amounts and types of interaction are happening on the site. This quantitative data, or WHAT data, coupled with the WHY data coming from UX and usability testing gives us a comprehensive view (or what I refer to as a 360 degree view) into website activity.
When analyzed together, this 360 degree view provides the necessary information to make far more informed decisions as to where website issues are, and why they are happening. The result of this analysis leads to better optimization recommendations and improved website conversion.
Types of Behavioral UX Data:
Conversion data from Google Analytics, CoreMetrics, or related log file analysis tools – This data is typically what your business cares about a LOT. Conversion data is used by Marketing, Product, Sales and Support teams to evaluate how well the website is attracting and ‘converting’ visitors into possible customers.
PPC Keyword Data – PPC Keyword data is a good source of information that helps define what search terms are attracting visitors to your website. Understanding what search terms are attracting website visitors and whether those visitors are turning into customers or not is important for understanding certain UX behaviors (like bounce rate, time on page, and others). Search terms that either are or are not attracting visitors need to be analyzed and understood. Search terms that are attracting but not converting visitors into customers is a primary way to identify optimization opportunities.
Bounce rate – The bounce rate for content pages can tell you how well your content meets the needs of your website visitors. Bounce rate is the number of visitors who land on a page, then immediately leave (ie, ‘bounce’ away). This website behavior often occurs if website visitors thought they were going to find certain content on your page, but when they got there did not find it and so left, often never to return. It can also tell you whether your website engagement and information scent are effective, or ineffective, for directing website visitors to the correct content.
Visits by Browser – When evaluating the user experience of a website it is important to know what browsers are the most commonly used for viewing site pages. The user experience of the site should work well for most browsers, but the most common browser should have special attention to ensure that experience is as optimized as possible. It’s dangerous to make optimization recommendations without first knowing how those changes will impact visitors using your most common browser.
Other types of Behavioral Data:
Session Duration – Time spent per session
User Flow – Top navigation flow for website visitors
Screen Resolution – Top screen resolution sizes your website visitors are viewing your site with
Etc. Etc. Etc. – There are literally hundreds of other data elements that can be analyzed. Which ones you choose depends on a number of factors including; the type of analysis needed, the type of website being analyzed (B2B, B2C, eCommerce) and the typical website engagement experience of your visitors.
Behavioral Data Examples:
Here are a few Behavioral data examples that can help explain how to acquire the WHAT quantitative data for UX optimization.
Visits by Browser:
The above Visits by Browser example helps you identify the most commonly used browsers your website visitors use when visiting your site. In this example, among US-based visitors the most commonly used Browser was Safari. About 50 percent of all website visitors used Safari to access the site. The next most common was Chrome at about 25 percent. A distant third was Internet Explorer at about 9% of all visitors. This information clearly demonstrates that although the website should work well for all browsers, emphasis should be placed on ensuring the UX is maximized for Safari.
A very helpful, but rather hidden report in Google Analytics is the Session Duration report. This data can be used to determine the engagement level of website visitors. In this example, the vast majority of website visits are less than 10 seconds long. In second place are visits between 181-600 seconds (3.1 minutes to 10 minutes long). In a very close third place are visits between 61-180 seconds (1.1 minutes to 3 minutes). This data is not necessarily bad or good. By combining this data with other behavioral data the true picture of whether this is positive or negative news will be defined.
The Behavior Flow graphic from Google Analytics is a good way to determine how well your ‘information scent’ is working. The most visited pages in the flow are across the top row of this report.
If that flow matches your most important website flow then congratulations, your website has an effective information scent. This by the way is fairly rare in the hundreds of behavioral data audits I’ve conducted.
Instead, the more common behavior flow as documented above includes several attempts to use the search tool to find information (as shown in the second most common interaction coming from the Default home page Starting page). This means visitors are using the website Search tool to find information.
Again, this may be good or bad news, depending on the type of site and whether other behavioral data points to website visitors getting ‘lost’ and resorting to search.
The three behavioral UX data examples above are just the tip of the iceberg in terms of the types of information that are available for analysis. By using the appropriate behavioral data elements in an analysis of website activity you can uncover the all-important WHAT IS HAPPENING quantitative data.
Conclusion: Behavioral UX Data Analysis
Behavioral UX data is a very effective way to analyze the quantitative WHAT IS HAPPENING information on your website.
Types of behavioral data include; conversion data from ERP & Google Analytics, PPC keyword data, website data including bounce rate, visits by browser, session duration, behavior flow, screen resolution and many, many more. Although UX behavioral data is very helpful, this quantitative WHAT data is not enough.
Although we know WHAT is happening, we still don’t know WHY it is happening.
Without this WHY information, any suggestions for optimizations are dangerous, as you are forced to guess why the behaviors are happening. Rather than guess, there’s a much better way to find this all important WHY (or qualitative) data. We must switch to qualitative UX research or usability testing to uncover the WHY for the observed WHAT behavior.
By conducting UX research or usability testing, we can begin to understand the WHY that helps us make sense of the WHAT behavioral UX data we’ve already documented. Combining both of these data elements (quantitative and qualitative) provides us with a far more accurate set of information with which to make optimization recommendations.
Conducting Behavioral UX Data Analysis is Step 2 of the 4 Big UX Optimization Steps:
The 4 Big UX Optimization steps are:
- Step 1 – Define Personas
- Step 2 – Conduct Behavioral UX Data Analysis (this article)
- Step 3 – Conduct UX and Usability Testing
- Step 4 – Analyze Results and Make Optimization Recommendations