What is the Best Way to Analyze Digital Body Language?

granify what is the best way to analyze digital body language 

You have a new customer on your e-commerce site. So far, they have viewed a few product pages, added one item to cart, and continued to browse. Then, their mouse movements slowed down. What does this mean?

Customers leave behind tons of information as they view your site. Every mouse click, swipe, and scroll makes up their digital body language—it means something. The challenge is figuring out what it means and doing so in time for that information to make an impact. Fortunately, machine learning technology has proven to be the right tool for the job.

In this article we will discuss what digital body language is, how and why machine learning is the best way to analyze it, and what makes this valuable.

Digital Body Language Means Something

Digital body language is can be understood as the digital version of body language.

Check out this article for a more in depth description of digital body language.

In person, we can read each other’s physical body language to understand if someone is interested, disgusted, excited, and more. A lot more. An eye roll, a smile, deep breaths, short breaths, the direction someone is pointing their feet—these all mean something. The context of when and where these body language cues are given also means something: think tears of sorrow compared to tears of joy.

Online, we exude our feelings and intentions through our digital body language. In the opening example, our new customer suddenly had a drastic change in mouse movement speed. Does this mean that she is almost done, concerned about the cost, or trying to figure out what else to buy? It’s hard to tell.

Our brains evolved to understand body language cues subconsciously, but we lack the ability to recognize much significance in digital body language cues.

Machine Learning Technology Can Make Sense of Digital Body Language

To understand the digital body language of our online customers, we need a way to analyze every mouse movement, keyboard click, page view, all the parts in between, and the context in which they happen. So far, machine learning technology has been the winner.

Machine learning technology is able to capture user data at scale and identify behavior patterns. This means that the hundreds of minuscule data points a single user generates every second can be quickly identified as similar to an online shopper that will abandon cart, similar to an online shopper that will convert with additional information (and identify the exact information needed), or any other distinct online behavior.

Machine learning technology can then be paired with the ability to act on the insights it reveals. So if our example customer slows down her mouse movements, the machine learning technology could distinguish that it means she is concerned about the cost of an item in cart and change the UI to remind her of the the limited time she has to take advantage of a special promotion.

Contrast this to what a skilled human analyst can do. Even if the behavior is identified, it takes time to crunch the numbers and the customer would have left the site before any action could be taken. Machine learning technology not only is better at identifying a pattern, it tightens the feedback loop.

Another advantage of using machine learning technology in this scenario is that it can work without the user signing into their account. Useful information can be discerned from the way a user behaves on your site, with or without a profile detailing their demographics, interests, and past behavior.

What is the Value of Digital Body Language?

Now that you know what digital body language is and how to analyze it, the next question is “Why?” Why should any business concern itself with understanding the digital body language of its customers?

By understanding what your customer needs (in terms of products and information) in order to buy today, you can increase revenue.

Companies that do business online are limited in how they can engage with individual customers. The physical separation between the online business and online customer prevents the business from learning who the customer is and what they need in that moment. And doing this at scale only compounds the difficulty of the challenge.

Digital body language is an often untapped resource of information about your customers that can help to identify needs and offer precise assistance.

When a customer walks into a pharmacy looking like they’re sick—you can point them in the direction of the cold and flu isle. When a customer enters an online pharmacy, do you know where to guide them? Maybe they’re there for bandages, contact solution, or to print photos. By using machine learning technology to analyze your customer’s digital body language, you can identify their needs and act with a high level of personalization, at scale!

 


Speak to one of our experts to see how Granify can help you analyze digital body language. 

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