Oct. 2, 2020
Retail shrinkage is a multi-billion-dollar sore fundamental problem in the retail industry. According to the National Retail Federation, in 2019, the inventory loss due to shoplifting, employee theft, or other errors and fraud reached $61.7 billion in the United States alone. To overcome the issue, retailers have implemented various loss prevention strategies and techniques, from electronic article surveillance, reporting systems, surveillance cameras, and plenty of policies to control the shrink.
Yet, they still fall victim to shrinkage, and most of these methods are reactive and tend to be inefficient, cost-wise.
The growing volumes of data have led organizations to use available data more effectively by developing systems to report, analyze, and predict shrink accurately. Thus, embracing advanced technologies such as artificial intelligence and edge AI devices.
Retail shrinkage can drastically impact retailers’ profits and might even put them out of business as the risk gets high for businesses that already have low-profit margins. The higher it gets, the more it can impact organizations’ ability to pay their employees and their business-related expenses, which eventually leads to poor customer service and experience.
Loss prevention drives higher profits and more business growth for the retail industry. It is a prime priority for retailers to increase their profits and decrease losses, and Retail AI Solutions are promising in retail loss prevention. These advanced technologies are using data patterns and insights to predict fraudulent activity in forms of shoplifting, internal theft, return fraud, vendor fraud, discount abuse, administrative errors, and so forth. Hence, providing a more proactive approach to reduce retail shrink and loss.
Retailers are now shifting to AI-driven solutions that allow an extensive set of opportunities to improve the customer experience as well as enhancing retail security by preserving protection against fraudulent elements of inventory loss and delivering a more reliable shopping experience.
Edge AI solutions such as video analytics can run instantly and effectively respond to events and actions occurring at the store.
There is a significant shift in how Edge AI approaches the loss prevention strategies from reactive to proactive, predictive prevention techniques. The process starts with collecting data from various sources, including security systems (camera, alarm records, etc.), video, payment data, store operation data, point of sales, crime data (local crime statistics), and supply chain data.
The data serves as a fundamental feed to leverage techniques such as computer vision, deep learning, behavioral analytics, predictive analytics, pattern recognition, image processing & recognition, machine learning, and correlation.
Integrating Edge AI in retail loss prevention offers a set of proactive actions to stop retail loss, increase KPIs to prevent inventory loss, discount abuse, pilferage, shoplifting, theft, and return fraud and reduce shrinkage. Moreover, it shifts the strategy from “Identifying a case” to “Preventing a case.”
Video analytics powered with artificial intelligence and machine learning algorithms allow retailers to overcome the limitations of traditional video surveillance systems. Artificial intelligence makes video searchable, and actionable enabling its users to proactively investigate the retail loss and pinpoint persons susceptible to committing the retail crimes, as well as offering real-time monitoring and alerts system for suspicious behavior.
Smart shelves are using technology to connect to the items they hold to monitor and secure these areas. Smart shelves are configured to provide real-time alerts and trigger calls to action for any abnormal activity detected. Beyond the loss prevention benefits, smart shelves enable retailers to track merchandise in real-time, giving insight into when to restock.
RFID-enabled smart tags attached to goods communicate with an electronic reader to track products. These devices can be removed at the checkout; if they’re not removed, a security alarm is triggered when the customer tries to exit the store.
An automated point of sale, or POS, is ideal for mitigating employee temptations to steal and help implement reliable inventory practices. Traditional systems are managed by employees. Still, failure to scan items is one of the primary ways employee theft occurs. Moreover, by not scanning a product at the checkout, employees are also discrediting inventory visibility.
The future of retail loss prevention is AI-driven. When used accurately, artificial intelligence is able to limit retail loss and manage inventory to overcome shrinkage and impact the bottom line. Are you looking for a reliable partner to strengthen your shrinkage prevention strategy with AI?
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The Chooch Visual AI platform offers a wide variety of brick and mortar retail AI applications. From shelf space management to in-store health monitoring, from image optimization to analyzing consumer behavior, visual AI can improve consumers’ shopping experience and revenues. The flexibility and efficiency of Chooch AI can deliver multiple impactful solutions to the retail industry on one platform.