Incidents of retail theft are increasingly making headlines, along with videos of thieves brazenly taking complete shelves of goods. Even more alarming, store associates who have attempted to detain suspected shoplifters have been harmed in the process.
Many retailers in large cities have resorted to putting often-pilfered items in plexiglass cases, which creates significant friction and aggravation.
These incidents of theft also are having an off-putting effect on consumers. A recent Coresight Research survey found that 26% of consumers would shop elsewhere and another 26% of consumers would move online if their local store put items under lock and key. Some 75% of surveyed consumers are concerned that retailers will raise prices to cover the cost of increasing retail theft.
The term shrink covers all inventory that has gone missing, yet nearly two-thirds relates to theft, with 37% accounting for external theft, including organized retail crime (ORC), and 28.5% owing to employee/internal theft, according to the National Retail Federation (NRF)’s “2022 Retail Security Survey.” In that survey, retailers recorded a 26.5% increase in ORC incidents.
Deterring Retail Crime
Although retailers cannot stop a determined shoplifter, there are measures that retailers can take that can help prevent some retail crime and, when it occurs, quickly minimize and recover from its impact.
Computer video, powered by artificial intelligence (AI), is an extremely powerful tool for loss prevention and protecting store associates. As a picture is worth a thousand words, am image of the suspect leaving the store with the goods is irreplaceable, and combined with item data, it provides a necessary piece of evidence for a criminal complaint.
Computer video can also help discourage thieves and protect associates. It can detect loitering, shelf sweeps, threating behavior, and track activity and license plates in the store parking lot. This application is not facial recognition, which generates many privacy concerns.
Tagging items, particularly with RFID tags, is the other key technology for loss prevention. It gives retailers visibility into their inventory and quickly adjusts inventory counts to account for what was taken. Readers mounted above entrances and exits can detect what was taken, when it was taken and via which exit, which can determine if it was an internal or external theft. The departure of an unpaid item can set off alarms or send alerts to store associates, and the data provides the other key piece of evidence for a criminal complaint.
There are other types of software that leverage AI and analyze data in the background. Prescriptive analytics software compares actual store sales data with baseline figures and can identify many types of theft, fraud and noncompliance.
Sweethearting — giving unauthorized discounts to friends — is one example of anomalous pricing that this software would pick up.
There are many other powerful applications of AI around the corner, owing to AI’s ability to automate the finding of relationships, even hidden ones, among large amounts of data. The advent of generative AI will likely enable even more new ways to analyze store activity to prevent theft and fraud.
John Harmon is the senior retail/technology analyst at Coresight Research. For more information visit https://coresight.com/.