Frannie walks into a furniture store, sits down on a small white couch, bounces once, and gets up. She then walks across the showroom, ignoring many other couches entirely on the way, and arrives at a big blue couch. She sits, bounces once, smiles, bounces again, and leans back into the decorative pillows.
A salesperson see’s this, walks over to Frannie and says “I see you like this big blue couch, did you know…”
In this story, the salesperson observed many cues from Frannie’s body language to understand her preferences, when to approach her, and how to personalize her experience.
Unfortunately in e-commerce, we don’t see body language the same way and can’t act on it either.
However, there is digital body language. In the same way that you and I broadcast our physical body language, we also input our digital body language when we are online.
If a savvy marketer or salesperson knows how to capture, interpret, and act on digital body language, they can personalize customer experiences much in the same way it is done in physical stores. But there are many challenges in doing so.
This article will go over the fundamentals of digital body language so that you can take steps to incorporate it as part of your e-commerce strategy.
The Definition of Digital Body Language
Digital body language comprises of all the digital actions a person takes while using a website, software or other digital tool. This includes deliberate and passive actions. Examples of deliberate actions are opening an email, clicking a hyperlink, or making an online purchase. Examples of passive actions are hovering over a button, leaving a page open and idle, or partially scrolling down a page.
Digital body language is viewed in the form of data, and depending on how much data is captured, marketing and sales teams can get a clearer picture of who their prospect is, what their needs are, and how to provide an optimal experience for them.
In e-commerce, a site visitor’s digital body language can reveal what they are interested in, their hesitations, and more.
Comparing Digital Body Language to Physical Body Language
Physical body language and digital body language are not so different. Whether you like it or not, your body language broadcasts clues about you.
When you walk into a store or begin negotiating a deal in a boardroom, the way that you hold your body, the nuance muscle movements in your face, and more give away your intentions, mood, and feelings about the situation. A hard eye roll, a big smile, these mean something entirely different. These are body language clues that tell the sales rep that you are not ready to buy or are about to be their best customer.
Digital body language is also an unconscious display of yourself and your intentions. By carefully observing your deliberate and passive actions, we can determine what products you are interested in, what motivates you to purchase, what information you need to see before buying, how likely you are to buy, and more.
How Can Digital Body Language Be Used in E-Commerce?
E-commerce companies that have the technical ability to capture, interpret, and act on digital body language are able to better personalize the customer’s experience.
For example, if a visitor exhibits a specific pattern of mouse clicks and page scrolls (a gross simplification) that reveals they need to know about a return policy before they purchase, you can then target them with a message that explains the return policy. In this case, the observed digital body language was passive.
Another example could be that an online shopper views kitchen items, but not clothing. You can use these deliberate actions to personalize their experience by recommending more kitchen items and avoid showing clothing items.
Ultimately, by being able to identify and act on a shopper’s digital body language, you can personalize your shopper’s experience, increasingly their likelihood to buy, customer satisfaction, and perception of your brand.
Challenges in Capturing Digital Body Language Data
The usefulness of digital body language depends heavily on the granularity of data captured.
Google Analytics captures aggregate data, showing you how many sessions, the average time on page, etc. But this doesn’t show the digital body language of individuals. You can use this aggregate data to optimize a site, but not a journey.
There are other platforms out there, Salesforce and Hubspot are among the most popular, that can keep track of an individual’s deliberate actions. The e-commerce company can use this information to trigger automated systems and to reach out to a prospective customer directly, already aware of their interests.
It’s more challenging to capture passive actions—and even more challenging to interpret this data. But think about this like you would with physical body language, the nuances of facial expression, while harder to pin down than say, clothing choices, still tell valuable information about the person.
Another challenge for capturing digital body language has to do with how much you know about the customer in the first place.
When someone enters your website and logs in or already has a cookie, it makes it a lot easier to connect all their actions to their profile. You can then use their profile information to learn about, segment and target that customer.
But most browsers have not logged in to their account. Without a cookie or pixel, you become practically blind to their digital body language. They drift in and out of your store and you lack the ability to personalize their experience. To be able to overcome this challenge, you need to be able to act in real-time, with only the information from that session.
Challenges in Interpreting Digital Body Language Data
As mentioned before, aggregate collections of digital body language will only tell you the average experiences on your website. This doesn’t qualify as digital body language or help with personalization.
Interpreting a single user’s deliberate actions is relatively straight-forward. Picture a timeline of deliberate actions that show that a user views pages only within the “Red Shoes” category. Their digital body language is clearly telling you they are interested in red shoes.
A single person can look at this and make assumptions about the shopper. A sales rep would use this digital body language cue to focus on red shoes. A deliberate action like this could also trigger an automated system that sends emails featuring red shoes.
Passive actions are exceptionally difficult to interpret, but if done well can tell you much more about the shopper.
If you had a timeline of every scroll, click, hover, double click, etc., it will be hard to make an accurate assumption from this information. And the more granular that information is, the more difficult it is to interpret it.
This is why recent advances in machine learning have propelled the use of digital body language in marketing and sales campaigns. A system powered by machine learning can detect patterns that might be hidden from even the best of human analysts.
Granify uses machine learning to understand and act on a shopper’s digital body language in real time. Request a consultation to learn more.