Smart Retail

Smart devices, RFID and the Internet of Things are on the rise in retail, providing new and better ways to meet the needs of connected shoppers.
Published: August 26, 2018

Smart devices are becoming more ingrained in today’s technology-obsessed culture as we embrace the Internet of Things (IoT). In retail, digital fitting rooms, interactive displays, smart shelves and RFID ceiling readers are beginning to move beyond the drawing board as retailers start to acknowledge the benefits of improved customer service and greater revenue from near-100 percent inventory accuracy.

After digitally connecting nearly two billion items of clothing and footwear, we’ve looked at the most popular IoT strategies that retailers are adopting to more accurately monitor the movements of goods, and to better understand consumer behavior. These include the increasing use of RFID tags fitted on every product or label (particularly in fashion), digital assistants or chatbots to offer assistance on customers’ smartphones, and staff members being armed with wearable technologies for up-to-the-minute information regarding exact stock levels, product recommendations and customer preferences.

Many of these latest technologies—such as automated self-checkouts (as used by Amazon Go) or Detego’s smart fitting rooms that utilize RFID sensors and interactive screens—are aimed at giving consumers greater ease-of-use and self-service options to improve the overall shopping experience (particularly in stores). This has forged closer ties to some of the more successful techniques spearheaded by online retail, such as personalized product recommendations, article availability checks, links to social media and product reviews, and omnichannel services like click-and-collect.

Connected technology gives real-world objects like merchandise a digital presence that can be closely monitored and analyzed. In order to integrate the customer into this picture, there are numerous technologies available: from simple footfall counters to camera-based systems, Wi-Fi or Bluetooth tracking. The main objective is to get more insights on customers and their behavior, in order to align customer service, adjust the product range and ultimately increase revenues.

Thanks to retailers keeping track of inventory and consumer preferences much more accurately using IoT and self-learning artificial-intelligence (AI) systems, fewer markdowns and lost sales will have a positive impact on the bottom line. IoT sensor technology (for instance, using RFID sensors in various forms) allows retailers to test product placements in stores and determine which articles are selected or tried on most frequently. Retailers can even offer customers the role of being a designer, personal shopper or trend scout, as another means of engagement and getting shoppers to share more information via social-media channels.

Customers, above all else, want instant and accurate information about product availability. If you’re shopping for clothes, you want to be sure you’re getting the exact size and style you’re looking for. But many retailers fall by the wayside here—their systems might tell them that a particular size is available, yet there’s a one-in-four chance that this isn’t the case.

We can reveal that the average retailer’s data is only about 75 percent accurate when it comes to knowing exactly what inventory is actually in stock at any particular moment. The problem is often compounded by retailers continually managing stock across multiple channels and increasingly having to stay on top of consumer demands for up-to-the-minute, reliable information. We found data inaccuracies around inventory to be more of an issue in fashion retail, in which ever shorter product lifecycles, fast turnarounds of stock and multiple styles, sizes and color combinations can play havoc with the supply chain and in-store operations.

Machine Learning and RFID
AI is ideally suited to forecasting and stock allocation. These processes historically tend to be quite manual and cumbersome, and generally are not managed that efficiently—largely because it’s just too much work to find the ideal mix for each individual sales location. It’s something that’s typically done by relatively small departments, even though product selection and stock availability is clearly fundamental to a retailer’s bottom line. Yet self-learning mechanisms can be put in place to maximize availability and promote what’s most likely to sell.

In most stores these days, store personnel are prone to stacking shelves based on whatever available sizes there are and what will fit, rather than having technology that knows what will be best for that particular store’s profit. By using AI, we’ve found that different stores—even in the same town—might require different sizes of garments to maximize their sales.

Continually relying on manual processes for something as vital to the retail business as stock—usually by shutting up the store once or twice a year for employees to carry out an inventory count—is madness. This is especially true given that smart technologies abound, including RFID and mobile devices, which ensure continual monitoring and 99 percent stock accuracy.

Research conducted by Italy’s University of Parma has shown consistent sales increases in RFID-managed apparel stores. The team deduced that “RFID item-level tagging is a powerful tool for improving inventory accuracy, which is a prerequisite for both omnichannel strategies and store floor replenishment from the back room.”

Thanks to technology that helps increase the availability of products on the shop floor—such as using wearable devices that rely on alerts and images to guide staff members, and to speed up the replacement of missing articles and gaps on shelves—the industry is starting to see a gradual shift toward more connected technologies in retail. IDC Retail Insights predicts that 80 percent of retailers are due to spend funds on visibility platforms powered by RFID and the IoT throughout the next few years.

Coupled with RFID tags on every item to help monitor stock levels with far greater reliability, AI can be used to improve on delivery performance and the distribution of inventory between stores, in the warehouse and even to the consumer. For example, we found one retailer flummoxed by hundreds of cartons of products having been shipped but never received, with various departments spending a long time trying to resolve the issue—a mystery that a machine could unravel within seconds. It’s not uncommon for retailers to not know exactly where stock is located at any particular time, but the joy of AI is ensuring that human mistakes are minimized—and that promises, such as a marketing campaign offering the latest product release at a special price at chosen stores, are always fulfilled.

In today’s digital age, customers have power over brands. This is a strong reason why retailers should consider bringing the IoT and RFID into their stores. IoT technologies mean shortened waiting times, better consumer engagement, higher sales conversions and more satisfied customers.

Dr. Michael Goller is the chief technology officer at retail software vendor Detego. He is responsible for the development and implementation of the Detego product suite, having handled numerous customer projects for various fashion companies. He’s a postdoctoral research fellow at Graz Technical University, where his chosen doctoral dissertation topic was “Probabilistic Modelling in RFID Systems.” Detego has produced a white paper about the Internet of Things, which can be downloaded here.