From RFID to merchandising, 3 ways retail data and analytics are changing the industry for the better
Retail data is king when it comes to streamlining back-end operations and optimizing customers' shopping experiences. Today, retailers are taking the guesswork out of day-to-day operations, from merchandise planning to creating store layouts, with the help of collected information and data analytics.
The following are three ways that the retail industry is using data insights to drive better return on investment (ROI) on their analytics software investment:
Radio-frequency identification (RFID) technology has been receiving renewed attention in retail as the digital revolution begets more sophisticated platforms, a development that has been a long time coming.
When the world's biggest merchant, Wal-Mart, went live with the technology in 2004, the retail sector held its breath in anticipation of the start of the RFID revolution. RFID was being heralded as the next generation of the bar code, as it could enable real-time product tracking through the supply chain, from merchandise supplier to distribution center to the store shelf. While RFID technology had been deployed on toll roads with E-ZPass, it was largely untested in the retail space.
The revolution never materialized. It turned out to be cost-prohibitive for suppliers, and since then, it has been applied merely in fits and starts. Now, RFID is once again promising return on investment for retailers in the era of big data.
Levi Strauss & Co., for instance, recently rolled out a RFID-enabled inventory tracking system in some of its stores. The program is designed to boost inventory accuracy by offering real-time product visibility to all relevant staff, from the executive team and supply chain managers to the stylists in each store.
Levi's advanced inventory tracking is not only about minimizing out of stocks, a palpable sales drain for retailers. It also provides insight on merchandise conversion patterns, essentially providing tracking tools for brick-and-mortar stores "that mimic some of the best of e-commerce," Yory Wurmser, an analyst with digital research firm eMarketer, explained in an interview. "With RFID tracking, Levi's can add new metrics, such as product-level conversion rates or fitting room abandonment rates, that can let them better design their stores and merchandising."
What's more, the system also offers the potential to improve real-time inventory tracking in a way that can inform local product search, Wurmser said.
2. Improving store layouts
Stores can also leverage retail data to maximize sales per square foot, a key metric when it comes to measuring return on investment. For instance, U.K. pharmacy chain Boots is using analytics to conduct ongoing experiments that test the optimal layouts for its stores. Using analytics, the retailer can estimate layouts and display techniques that will work best to achieve a particular goal, Information Age explains. The process involves mining data to answer questions such as, "Does it make sense to install a product kiosk to give consumers easy access to inventory?"
The insights gleaned from analytics on optimal layouts and merchandise displays can also help retailers make more informed operational decisions, such as the allocation of in-store labor and sales associate training needs.
3. Better behavior insights with IoT
Stores are increasingly turning to retail data collected from Internet of Things (IoT) devices to generate meaningful, measurable insights on customer shopping habits and buying patterns, which can then help them make better merchandising and marketing decisions. Take intelligent shopping carts, for example. With shopping carts connected to IoT networks, retailers can track customers' movements through a store and note where people tend to linger. Retailers can use this behavior data to maximize inventory levels for hot products and measure the effectiveness of special displays.
For instance, if a particular store area is not well trafficked, "a retailer may rearrange the merchandise to attract more activity and more sales," according to the Platt Retail Institute. Real-time data can also be used to improve the shopping experience by helping staff predict when consumers will reach checkout lines.
These are just a few of the ways that retail data analytics can help stores to make informed decisions on merchandising, store layout and inventory. With more efficient operations, retailers can optimize their ROI, thereby remaining ahead of their competitors in the fast-paced industry. Enlist the cognitive power of analytics tools through IBM's Industry Solutions for Retail.