Observational Data and the Web Analytics Ecosystem: Part 3
In my first post in the series, I shared a bit about the important role observational data plays in the web analytics ecosystem. In Part 2, I shared a few examples of how our clients have used this kind of data.
Today, I want to talk a little bit about how observational data (session replays) helps web teams to be more efficient.
The ability to watch replays of your users’ sessions – including their mouse clicks, scrolling, form entry, where they pause, and where they hover – speeds up the identification, acceptance, and resolution of site issues like nothing else I’ve seen. What used to take months to fix can now be addressed in weeks, because not only can you see with your own two eyes what the problems are, you can share the replays with others on your team.
ACCEPTANCE: Our clients have confided in us that prior to using ForeSee’s SessionReplay, when they tried to push for particular improvements based on customer demand to their development counterparts, the developers would often not be able to recreate the issues that drove the need for improvement or did not agree with the information architecture changes that were being suggested. With SessionReplay, these requests for site enhancements that used to cause hours or weeks of internal debate can now be plainly seen by both groups, and resulting site updates are agreed upon much more quickly, which equals a far more condensed time frame for resolving web issues.
RESOLUTION: Once you figure out what the problems are, showing the replays to others in your organization (which speeds up buy in, support, and budget for your suggested fixes) creates huge efficiencies on your team. In addition to realizing which fixes need to be made much sooner, your development team members will spend less time in meetings discussing problems and solutions, and they’ll have more time to actually fix the site issues.
Some of our clients have seen increased efficiency by actually replacing focus groups with SessionReplay. Focus groups are costly and time intensive. Whether you contract the focus groups out or handle them internally, tremendous time and effort must be spent deciding on what types of people to bring in, what to show them, what to ask them, etc. Having user sessions on demand within the ForeSee portal puts a representative sample of your site visitors at your fingertips. This “focus group on the fly” can be created in minutes by using quick and easy filters within the portal.
The filter works like this, and it is part of the secret sauce that makes ForeSee’s session replays so effective and useful. First, you use the ForeSee methodology to tell you which area is your highest priority. Let’s say it’s navigation. You filter your session replays by looking only at people who rated navigation extremely low. You’ll end up with thousands of user sessions—way too many to poke through to try and find the needle in the haystack.
Although that first step seems pretty intuitive, it’s one of the main things separating our session replay technologies from others on the market. Others can help narrow sessions by showing you behavioral data—who did or didn’t buy—but you can’t filter by customer attitudes, which is the real key.
Next, you know that first-time users are an important segment for you, so you filter by first-time visitors who gave navigation extremely low scores. Also, you know from looking at open-ended comments that people are having a particularly hard time finding matching accessories. So you can filter by first-time visitors who gave navigation low scores and also mentioned finding accessories in their open-ended comments.
The result of this filtering will be a handful of highly specific, highly valuable user sessions that will give you great diagnostic capabilities. Show them internally, and you’ve just sped up that whole process of identification, acceptance, and resolution without having to bring people into an artificial environment.
In addition, ForeSee SessionReplay now includes heat mapping – a visual representation of the aggregate interaction on a given page of a site—so, for example, you see a shot of, let’s say a page of national news, and you will see the areas with a lot of click interactions, mouse movements, or viewable page components as red, and you will see the areas with very little interaction as blue. Our heat maps are also easily segmented based on the same filters that are set up to view the replays themselves. Imagine being able to see click maps, mouse movement maps and page scroll maps of your first time visitors vs. frequent visitors or those coming to make a purchase vs. those just coming to browse and the usability insights gained from the different ways those users interact with your site. It’s pretty cool functionality created by our team in Vancouver that we’re pretty proud of.