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Safe and Secure How AI can help chase shoplifters and protect profits By Kathleen Garner
Kathleen Garner, a strategic customer success manager at Appriss Retail, spent more than 13 years in Loss Prevention leadership at Kmart and Sears.
Picture a store associate stocking shelves down a narrow aisle. Nearby, they spot a shoplifter concealing a few cans of baby formula and sprint toward the exit. What’s their next move? Run after the thief in a crowded store or stand down?
products with locked cords. It’s not a great look on-shelf, and the practice could deter consumers. Keeping associates safe is a priority for retailers, so to combat retail theft, they need to lean more into technology to stop shoplifters.
Decades ago, store managers expected staff and security to chase after shoplifters, but that sentiment has changed. For the safety of employees, running after a shoplifter isn’t worth the risk.
For a long time, security cameras have been used to record shoplifters. But with technological advancement, they can now leverage computer vision capabilities to do a lot more.
According to the National Retail Security Survey from the National Retail Federation and Loss Prevention Research Council, more than two-thirds of respondents said they experienced a spike in violence and aggression from bad actors in stores. So, what’s a retailer to do? A strong alternative to pursuing shoplifters on foot is to enable AI-powered technology to do the chasing. Some of the most shoplifted items sit on shelves in drugstores. The NRF security survey listed diapers, formula, alcohol, candy, energy drinks, cosmetics, pain medicines, vitamins and personal care products as frequently targeted items. Plus, pharmacies tend to have small footprints, enticing a quicker in-and-out. The NRF and LPRC security survey also reported that: • 70% of retailer executives surveyed are seeing an increase in repeat offenders. • Shoplifting incidents often involve around three people working together. • Smash-and-grab shoplifting attempts can be the most violent. To limit theft, many stores resort to locking up items behind plastic cases. They’ll also tie up detergent bottles and other
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They can identify and notify staff of any suspicious activity occurring in real time along an aisle and use facial recognition to identify a known shoplifter or computer vision to analyze a license plate on a car that a shoplifter used to flee a store. Cameras keep watch and can follow bad actors beyond the store to help law enforcement. Additionally, AI-powered technology can monitor transactions for unusual behavior, particularly identifying a shoplifter who looks to return stolen items at another store. AI-powered models can also read through an abundance of store data, such as receipts, returns and inventory to quickly identify suspicious activity and alert investigators of the cases that are most likely to be resolved. Theft inside volatile retail channels can account for nearly 70% of a retailer’s shrink, according to the NRF and LPRC security survey. The report said in 2022, shrink equaled $112.1 billion in losses, up from nearly $94 billion the year before. AI detects theft cases that were missed in a store and can discourage associates and security from pursuing shoplifters they spot. Enable technology to do the chasing for loss prevention teams and help reduce the dramatic financial impacts that theft can cause on a retailer’s bottom line. dsn