Self-checkout is having a moment. What is the current state of self-checkout technology in retail stores?
Self-checkout, once a novelty, has become a ubiquitous feature in many retail stores. These systems have advanced significantly over the years, incorporating technology such as barcode scanning and weight sensors to detect items that were not scanned through the self-checkout but placed in the bagging area. They also have seamless payment processing capabilities. Some retailers even employ sophisticated AI-powered algorithms to accurately identify items without barcodes, such as produce, and to help reduce theft.
But, this convenience-forward feature is having a moment that should cause retailers to pause and reflect on their self-checkout strategy. In October 2023, Walmart removed kiosks from three of its stores. Early this year, Kroger ended its self-checkout-only experiment in Dallas. Other stores, like Target and Dollar General, have also made adjustments to their self-checkout procedures.
Much of this has to do with the fact that retailers are facing a shrinkage problem. While self-checkout systems offer convenience and efficiency to customers, they also present opportunities for theft and fraud, both by customers and employees. A 2023 survey by The National Retail Federation found that inventory shrink increased by 13.2% between 2022 and 2023.
How should retailers look to combat shrinkage problems?
15% of shoppers say they’ve stolen items while using a self-checkout kiosk. 44% said they would do it again. 61% of shoppers who accidentally take an item would keep it anyway.
To address the issue of shrinkage, retailers should focus on advanced self-checkout technology. This includes customer-facing cameras, manned self-checkout, and anti-theft tech. The cameras let customers see themselves as they checkout, manned self-checkout kiosks have cashiers who frequently help and look out for theft, and anti-theft technology stops customers from finishing transactions until they scan all items.
Inventory management is crucial to understanding whether a retailer has a problem — they need to have accurate shrink numbers that can be classified as theft. Other measures retailers can take are optimizing store layouts to enhance employee vigilance and maintain merchandise organization; employing advanced security measures, like surveillance cameras and RFID tags on high-theft items; and promoting employee training programs that emphasize theft prevention and how to manage inventory efficiently.
Aside from managing shrinkage, what are some other ways that retailers can optimize their self-checkout experiences?
Retailers can elevate their customers’ self-checkout experiences in a variety of ways. From a technology standpoint, they can use AI to analyze data gathered from self-checkout systems. This can unlock valuable insights into customer behavior and transaction data, which can uncover hidden patterns and trends that show how customers are interacting with the store’s products. Some self-checkout systems are only used during busy times when there are lines, while others are used only for one-off items or to optimize third-party delivery services like Instacart or DoorDash. There are lots of different ways self-checkouts are used around the world, and it is up to retailers to build units that are optimized for their clientele.
AI can also be used for predictive maintenance of self-checkout kiosks. The retailer can monitor for system failures so that the machines remain operational, minimizing downtime and providing a seamless customer experience. Robust employee training also ensures retailers are aware of when customers need prompt assistance for any technical issues that may arise.
Additionally, retailers can invest in user-friendly interfaces and intuitive designs for the kiosks.
As AI and machine learning technologies advance, how can retailers use this technology to remain competitive? Are there best practices for integrating these technologies seamlessly into stores?
Retailers must first consider what problem they are trying to solve when looking to implement AI and machine learning in their stores. For example, it could be something related to inventory where they are having consistent overstocking or under-stocking issues. Or maybe they’re having a hard time getting customers to return to their store and don’t have the insights to uncover the reason.
Once retailers have identified the problem they’re addressing, it’s crucial to actively engage in the industry network to learn what is out there to help them. Everything from attending trade shows to reading up on new products online to interacting with vendors helps build their education.
Then, with a clear understanding of how the technology can address their needs, careful implementation is imperative. For instance, a retailer could start with a pilot program that puts the technology in selected stores and assess its effectiveness before broader deployment.
Let’s go back to the examples listed above to discuss how AI can actually be used. To handle issues around consistent over or under-stocking, AI algorithms can analyze historical sales data and current market trends. Retailers can then forecast demand more accurately and ensure optimal stocking levels. This can reduce the risk of stock-outs, minimize overstocking, and ultimately maximize revenue. If retailers are looking to keep their customers, AI and machine learning technologies can help personalize the shopping experience by providing tailored recommendations, promotions, and product offerings that target individual preferences and behaviors. This ultimately drives increased sales and long-term loyalty.
How do you envision self-checkout evolving as stores are removing the technology from certain locations?
As some stores remove self-checkout technology, others may choose to improve and refine their systems to better meet customer needs. Amazon, for example, announced it is removing Just Walk Out technology from its Fresh stores and is pivoting to a different format – shopping carts with built-in checkout screens and scanners.
A lot of the automation is happening in the back of the house, reducing the need for labor, and freeing up the budget to hire hospitality-level service for the front of the store.
Where do you expect AI adoption in grocery to show up first?
AI is here and is being adopted by all of the major grocers. It’s showing up in price optimization and back-of-house automation like augmented ordering, demand forecasting, predictive labor scheduling, and more. It’s here to stay.
