dvance analytics helps beyond facial recognition

Over the past decade, advance analytics of security technology has evolved considerably. The analog cameras of the past are slowly but surely being phased out, and the familiar banks of monitors covering an entire wall of the security office are going with them. New technologies, in the form of both hardware and software, are helping businesses and organizations protect their people and property more effectively than ever. The rise of network cameras, video and sound analytics, thermal imaging, and more have enabled these organizations to revolutionize the way they approach security.

dvance analytics helps beyond facial recognition

This is especially true in the retail industry, where the benefits of improved security technology go far beyond the obvious loss prevention applications. Facial recognition technology due to advance analytics in particular has proven that it cannot only help retail locations protect their assets and employees but can have a positive effect on customer service capabilities as well. While it is important to remember that any new technology must be used in an ethical and responsible manner, facial recognition has more than demonstrated its ability to improve the retail experience not just for businesses, but for their customers as well.

Facial recognition of advance analytics goes hand-in-hand with advances in network camera technology, and as processing power has grown, so too had the ability to process data at the network edge—in this case, onboard a network camera. As cameras become increasingly capable of processing data, bandwidth requirements and processing power needed on the server-side for facial recognition become lower, making the technology easier than ever to deploy. As a result, an increasing number of brick and mortar retail stores are turning to the technology, with both large department stores and small to mid-sized businesses seeing the potential benefits.

When it comes to facial recognition of advance analytics, it’s no surprise that the first application many people think of is loss prevention. It is easy to imagine how a retail store might use this technology to deter repeat offenders and organized retail crime syndicates: known offenders that have been identified can be enrolled in a database maintained by the store, which facial recognition software can use to check against incoming customers. Knowing that the software will identify, and flag known offenders allow loss prevention personnel to focus their efforts on keeping their stores and employees safe and helps reduce false apprehensions and assumptions among employees.

Not only can identifying a known offender help a store prevent a problem before it arises, but it also empowers the business to decide what to do about it. This might come in the form of avoiding contact and calling the police or simply observing their behavior more closely than the average guest. Some stores even prefer the tactic of providing an identified offender with exceptional customer service, which has the benefit of allowing employees to keep an eye on the suspect without being conspicuous and may also lead to an uplift in sales.

It’s important to remember that theft is not the only problem that retail locations face. Armed robberies, while less common than run-of-the-mill theft, are a real concern for many retail stores—particularly those in more dangerous locations. While the ability to identify a known shoplifter can help retail stores reduce shrink due to theft, identifying someone known to have carried out previous armed robberies is considerably more important. This can be helpful even if the suspect’s face is obscured, as armed robbers tend to cover their faces. There are examples of stores in high-risk areas that lock their doors during evening hours when robberies tend to occur, notifying potential customers that security is in use and requesting that they face the camera. The door will only unlock if the camera detects an uncovered face that is not in the store’s database as a known offender. If they are a known offender, the store manager is notified so they can decide on the appropriate action to take.

All this talk of loss prevention and security might lead you to believe that facial recognition is all about “catching bad guys,” but that is far from the case. We’ve all seen movies in which a high roller arrives at a casino where they are greeted by name and provided every convenience and courtesy. Why do casinos do this? Naturally, it’s because that guest and their behavior are known to them. They know that guest is going to spend a considerable amount of time and money in their establishment, and they are eager to give them every reason to extend their stay.

Thanks to facial recognition technology, this type of treatment need no longer be confined to wealthy casinos and other similar establishments. The ability to identify frequent customers, or those who spend large amounts of money within the store, can alert employees to provide them with extra care and attention. Not only does this encourage customers to spend more time and money within the store, but it helps cultivate a relationship between staff and patrons. By identifying and alerting staff to the identity of the customer, information on previous purchases, clothing sizes, favorite or frequent purchases, and more can be called up, allowing employees to serve the customer’s needs more effectively. High-end clothing stores have found this to be a particularly effective use for facial recognition, and other retail verticals are hot on their metaphorical (and in this case, literal) heels.

The COVID-19 crisis has highlighted a number of other potential uses for facial recognition that are valuable in their own right but have seen their value rise amid the global pandemic. Integrating facial recognition technology with access control has uses that go beyond loss prevention—by training the software to recognize employees, suppliers, contractors, and others who might require access to the premises, it is possible to enable touchless access to stores. For instance, in the past, someone making a delivery might be granted temporary access with a keycard or key fob, but at a time when a global pandemic is still raging, touchless entry is much safer for all parties. With facial recognition, you are your own credential, and a camera that recognizes a supplier’s face can provide access to the building without ever needing to touch a keypad or other surface.

The technology can also be used “in reverse.” Today, many states and municipalities have instituted mandatory mask orders, requiring that anyone in public spaces must be masked to mitigate the spread of the disease. Whereas in a loss prevention context, facial recognition technology can be trained to flag those whose faces are obscured, in the COVID-19 world, the opposite may be more helpful. Facial recognition can instead be instructed to raise an alert when a customer without a mask enters (or attempts to enter) the store so that the appropriate action can be taken. In fact, Major League Baseball has reportedly explored this technology as they look for ways to welcome fans back into baseball stadiums around the country. If facial recognition technology can identify unmasked fans in the stands so they can be removed, it will likely go a long way toward helping other fans feel safe attending games once more.

Before we conclude, it’s critical to address the elephant in the room: there are certain negative connotations surrounding facial recognition, and conversations about how it can be used ethically are ongoing. These are important conversations to have, but it is also important to draw a distinction between the use of facial recognition in a law enforcement capacity and the use of facial recognition in a retail capacity. Ultimately, it comes down to how the technology is used, but the privacy stakes surrounding use of facial recognition in a retail environment are considerably less than those surrounding its use by law enforcement. No matter your feelings on the latter, using the technology to ban a known shoplifter from a retail store is undeniably different from scanning every face to check for outstanding warrants.

Ultimately, it is important for businesses to establish best practices with regard to how the technology of advance analytics will be used and determine how staff will engage with customers. In-depth training on the software (and associated company protocols) should be conducted before the technology is even implemented, and both retail employees and company leaders must be aligned. Perception is important and choosing a facial recognition partner with a reputation for ethical behavior and a commitment to helping train system administrators on the proper use of the technology is essential. The best way to overcome the negative stigma over facial recognition is to demonstrate clear value in its use. After all, how many of us use facial recognition to unlock our phones every single day? No technology, in and of itself, is the enemy. How it is used will determine its perception for years to come.

Loss prevention is an important use for facial recognition of advance analytics, but it is important to consider its more positive uses as well. The technology is more than just an eye in the sky keeping an eye out for “bad guys.” It’s a way to provide top-tier customer service to valued customers. It’s a way to keep both customers and employees safe in the midst of a global health crisis. And it’s a way to ensure smooth, frictionless entry to those who need it. True, facial recognition helps businesses pick out known shoplifters, but it can also help bridal shops remember the dress size of every bridesmaid, facilitate large deliveries with ease, and—maybe someday—help baseball fans snag home run balls once more. As the uses for facial recognition expand, it will be up to businesses to use the technology responsibly. If they do, the future of facial recognition and the retailers who use it will be bright indeed.

Originally published by Security Info Watch