- Sensormatic Solutions integrates machine learning into its Shrink Analyzer for improved loss prevention.
- The new features will be showcased at NRF PROTECT 2025 in Grapevine, TX.
- This enhancement aims to boost data integrity, identify suspicious behaviors, and improve investigation outcomes.
Sensormatic Solutions, a part of Johnson Controls (JCI, Financial), has announced the integration of machine learning (ML) into its cloud-based loss prevention application, Shrink Analyzer. This development aims to enhance retailers' capabilities in identifying and addressing internal theft and loss events with greater precision.
The updated Shrink Analyzer includes features such as Sweetheart Detection and a Shrink Confidence Score, which are engineered to improve data integrity by simplifying data aggregation processes and increasing accuracy. Approximately 49% of retailers using RFID technology for loss prevention prioritize these improvements, according to a study by VDC Research.
The machine learning upgrades will allow retailers to better detect suspicious behaviors among store associates, including sweethearting and scan-avoidance at self-checkouts. This is achieved by analyzing item-level sales, inventory, and behavior data, thus enabling retailers to identify and respond to evolving loss prevention tactics.
Moreover, the improved application is designed to help retailers increase the productivity and efficacy of their investigative teams, as well as accelerate prosecution timelines. With ML, Shrink Analyzer can now identify hard-to-detect loss events, facilitate video indexing, and automate case building, making law enforcement processes more efficient.
Sensormatic Solutions will present these advancements from June 23-25 at the NRF PROTECT 2025 event at the Gaylord Texan Resort in Grapevine, Texas. These enhancements will be available later in 2025, further cementing Sensormatic Solutions' leadership in retail loss prevention technology.
