Inventory loss, also known as Shrink or Shrinkage, is a BIG problem in the retail industry. Usually caused by shoplifting, employee theft, and neglect, this accounts for 2 to 2.5% of Sales, which means a lot of potential revenue disappearing into thin air. Add the Corona Virus pandemic to that and you have Health safety too in the Problem mix.

Which is why more retailers are developing and implementing strategies for their store and earmarking budgets into in-store security measures to track and deter inventory losses, improve performance and support safety.

Digital technologies are constantly projected as the answer as future-proof options for retailers. One of the most widely discussed technologies is artificial intelligence (AI), and one of the forms of AI most easily applicable to the retail environment is Vision.

How does Vision Intelligence work?
Artificial Intelligence in Vision is an emerging technology that enables retailers to harness the power of video to automate the process of identifying and alerting threats in real time. It attempts to enable computers to “see” and understand, in much the same way as the human eye and mind. Computer algorithms use deep learning models to process visual content received from cameras to identify and classify objects. They further analyse for distinctions such as shapes, colors, borders, spacing, and other patterns to build a profile in such a manner that the software will be use this learned data to find other images that match that profile.

Solutions for Shrinkage already exist
Vision Intelligence is already in use to provide traffic and behavior analytics by using real-time, accurate visitor counts and classification, so retailers can understand customer traffic by knowing a customer’s path through the store, where they spend time, and how much time is spent there. Its deep-learning features also provide insights into behaviors and demographics, which can help in optimising marketing, sales, and rewards programs.

Facial recognition is another form of the technology that has been tested and proven in retail. It is particularly useful in helping retailers detect shoplifters and alert when known bad eggs are in the parking zone or about to enter the stores.

Advanced solutions have also been implemented that detect real-time potential loss of billing caused by BoB (unemptied items at the Bottom of the Basket/Trolley), or “Sweethearting” or “Buddy billing” (neglecting to scan all of a friend or family member’s items) or No billing at self check-out counters.  The software can also be taught to identify definitive pattern of habitual shop lifters, like loitering in parking lots, and to recognize actions like putting objects into a pocket or a handbag.

Pandemic Challenge
Existing Computer vision technology can be easily adapted to address challenges caused by the Covid pandemic, such as temperature screening, mask compliance, and social distancing. Thermal imaging, originally intended to detect intense heat for early indication of fire, can be used to screen temperature and detect elevated body temperature of individuals entering a facility. Mask detection used to identify a person as a robbery threat can be adapted to detect a face mask for health compliance. Facial recognition that helps to determine unique customer counts can also now allow retailers to stay within social distancing guidelines.

Investing small

Vision AI has the great advantage of being a flexible technology. Data with a visual context already exists. It is up to you to do what you want with it. Investing in solutions on a small scale to begin with makes absolute sense. That won’t prevent you from being able to expand its use seamlessly in the future, meaning it is future-proof. You can adopt a particular solution to integrate with your retail loss prevention method in any way that you think fit.

 

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