Face Recognition Software and its Importance to Retailers (Part 2)

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In our article last week, we looked at ways that face recognition software can help retailers with security issues such as shoplifting and return fraud. By mapping the faces of customers who are entering the store, face recognition technology can determine whether that person is a suspect or has been convicted of shoplifting in the past. Facial recognition can also help store security know if an item that is being returned was actually stolen from the store, and whether or not the person returning it is the one who took it. There are other ways that having a face recognition system can benefit store owners. Here are a few more facts about face recognition and its importance to retailers.

Those Cameras Aren’t Just for Security

We have discussed how face recognition connected to in-store cameras can help retailers combat theft and fraud. But once connected to a facial recognition system, those cameras aren’t just for security anymore. According to VIA Technologies, face recognition not only can identify and classify a retailer’s customers, but information such as the customer’s age, gender, and prior shopping habits can be learned through the system as well.

Retailers Can Learn A Lot from Face Recognition

With this type of system, a retailer can learn a lot, not just about each customer, but about his or her store as well. As the face recognition system keeps track where customers walk, where they stop, which products they looked at and put back, and which ones that they purchased, core data can be kept. This data helps the retailer learn how to optimize their store setup, how and where to place stock in the store, making the store easier for customers to navigate and placing the most sought-after items in high traffic areas.

It Can Even Determine a Shopper’s Mood

Face recognition algorithm is no longer just about identifying a person. It can also determine that person’s mood. Facebook has a program known as DeepFace that actually scans a person’s face as they scroll through their timeline. This program can determine the emotional reaction of that person to the posts that the person is seeing. That information can help identify which products a person is interested in, and which ones they are not likely to like.

This can also determine a person’s mood. If a person is happy, they are more likely to spend money. DeepFace could potentially be connected to the cameras in a retail store and allow the retailer to “recognize” the shopper and their mood as soon as they enter by connecting to their social media. The retailer would know which items are likely to interest the person, and even what their mood is. As Entrepreneur says, “Your shopper is sad today? Why not play her favorite song as she approaches the shoe rack?”

Those are just a few ways that retailers can use facial recognition to increase sales, decrease theft, and improve the customer’s shopping experience. Next week, we will look at rends in face reconition software.