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New Techniques to Prevent Shoplifting

Nov 14 / Dan Keller





The rise in shoplifting has become a significant concern for retailers, leading to substantial financial losses and creating challenges for businesses to maintain sustainability. Beyond economic impacts, shoplifting fosters an environment of insecurity for employees and customers alike. Preventing this issue is critical not only to safeguard profits but also to ensure safe and welcoming shopping experiences.
To prevent shoplifting, many stores are integrating advanced technology, employee training, and subtle deterrents to improve security without compromising customer experience. Here are some of the latest techniques.

 

1.  AI-Powered Surveillance Systems

  • Behavioral Analysis: AI cameras can now monitor shopper behavior patterns, identifying movements and gestures associated with shoplifting. The system can alert staff in real time to prevent theft.
  • Facial Recognition (where legal): This technology identifies known shoplifters or previously flagged individuals. Some systems alert staff if a high-risk individual enters the store.
  • Checkout Monitoring: AI at self-checkouts monitors product scanning and helps catch unscanned items or unusual checkout activity.

 

2.  RFID and Electronic Article Surveillance (EAS)

  • Smart Tagging with RFID: Radio-frequency identification (RFID) tags are widely used, but recent advancements allow more precise tracking within stores, identifying if an item Is taken without being paid for.
  • Integrated EAS Tags: More advanced EAS tags that are harder to remove and can work seamlessly with RFID enable real-time alerts if an item passes security gates without payment.

 

3.  Electronic Shelf Labels (ESLs)

  • ESLs allow rapid price changes and real-time inventory monitoring. They can be paired with sensors that detect item movement from the shelf, allowing the store to know when high-value items are removed or displaced.

 

4.  Shelf-Sensor Technology

  • Motion and weight sensors embedded on shelves can track item removal. This provides data on how frequently and when specific items are moved or removed, allowing quicker identification of high-theft items and periods.

 

5.  Customer Flow Analytics

  • Heat maps and customer flow analysis can pinpoint high-traffic and low-traffic areas. This data helps optimize store layouts to discourage theft by strategically positioning high-theft items in more visible areas.

 

6.  Mobile Device Integration

  • Some stores are experimenting with mobile apps that link directly to shopper identities and shopping carts. Known as “scan and go” apps, these systems create customer profiles, which may discourage shoplifting due to personalized tracking.

 

7.  Smart Fitting Rooms

  • With sensors, RFID tags, and cameras, these fitting rooms track items brought in and can alert staff if items are removed from the fitting room without reappearing in the store’s inventory system.

 

8.  Training for Staff Awareness

  • Using virtual reality (VR) or AI simulations, staff can be trained on situational awareness and common shoplifting tactics, so they’re better prepared to recognize and respond to suspicious behavior.

 

9.  Digital Signage with Real-Time Alerts

  • Digital signage near exits can display real-time alerts of flagged behavior, potentially discouraging shoplifting by reminding customers of the security measures in place.

 

Combining these approaches creates a multi-layered deterrence strategy that protects inventory while balancing customer experience.



ACPI is the worldwide leader in enabling law enforcement agencies, businesses, institutions, and security professionals to reduce criminal activity and risk and enhance quality of life through the delivery of practical, unbiased training and certification programs.  Visit our website at acpionline.com to learn about our comprehensive list of both live virtual and self-paced training courses.

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