What is Visual Analytics?

Steve BurgData0 Comments


When WalkMe purchased Jaco, we were referred to as a visual analytics platform. For those who work in the data field, this may have been a bit confusing as there is already a concept of data visualisation. While we will dive deeper into that topic on another day, this post will be focused on what visual analytics are and how they are used.


What is Visual Analytics?


Simply put, visual analytics platforms give you the ability to see not just who is using your platform (quantitative data), but also how they use it (qualitative data). While the quantitative data can tell you the who, what, and when, visual analytics providing you with valuable answers to the question of why. Using our software, you can view a pixel perfect recreation of every single user session that occurs on your platform.


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How is Visual Analytics Used?


Visual analytics can be applied in multiple ways and as we discussed in earlier posts are an integral part of the agile analytics formula. The two primary cases we’ve seen for visual analytics are used by the product and support teams.


Visual Analytics for Product Teams


While building the Jaco product, we engaged with product teams from companies across various verticals to ensure that we were answering their needs. The remark we encountered most often was, “I want to know exactly, and I mean exactly, how my users are engaging with my product.” That is what we set out to tackle.


After lengthier conversations, the real need became clear. Product managers spend, time energy and money building features for a product. As a result, it is crucial to identify which of the features they are being used, how often, and for what. They were eager to ascertain the success of existing features in order to determine the success of future products.


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From the agile analytic side, this is some serious 1st party data. Imagine having every department pointed towards a similar goal and how much more efficient that would make your company. It’s an unfortunate question to ask, but how often do you believe the marketing team receives use case examples (outside of case studies) to build out their targeting plans? From our experience, not close to often enough.


Visual Analytics for Support Teams


Not to toot our own horns here, but Jaco is one of our favorite implementations of agile analytics. In order for visual analytics to be used to it’s fullest potential, the data must be able to be used for multiple applications that are related but different.


So why would a support team need to see a pixel-perfect rendering of a user session? Simple. If our tech support teams were able to see exactly what a user did when something went wrong, it would eliminate the guesswork from tech support. This would drastically reduce support ticket times.


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The perfect example of agile analytics in action is a customer of ours, Unpakt. You can read more about their case study here but let’s focus on the part that matters. “While our support team does not rely directly on Jaco, it is utilized in our support and debugging process. By avoiding human error and imperfect memories, the ability to truly understand what triggered the event likely saves 90% of the effort to create a solution.”


When Should You Use Visual Analytics?


Now that we’ve examined what, how, and why, let’s discuss when visual analytics should be used. To us, it’s really quite simple. If you want to learn more about how your product is really used, you are ready for visual analytics.


There are many types of visual analytics, but at Jaco we believe that if you truly want to understand your customer, you need to step into their shoes. Jaco’s is the only technology that allows you to recreate your user’s experience. Heat maps may show you where they click, but it doesn’t tell you why, which is why we don’t offer them.


We believe that understanding the why adds a whole new layer of data to your aggregated field and answers many of the questions that our clients will ask.


In summation, visual analytics is quite different from data visualisation. It adds another dimension to the product analytics, one that will make entire companies more efficient.


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