In the years leading up to the Covid-19 pandemic, the most discussed topic in the retail sector was the Retail Apocalypse. A combination of the rise of e-commerce, overbuilding of stores, and too much debt-load resulted in thousands of physical retail locations going out of business. Iconic chains, like Sears and K-Mart, seemed to vanish overnight. Pini Mandel, cofounder and CEO of Quicklizard, observes, “Ever since Borders bookstore realized it could no longer compete in 2011 and shut down all 399 of its stores, there’s been a steady stream of iconic stores that folded. Over the last decade, e-commerce’s victims included Toys ‘R’ Us, the Sports Authority, and Pier 1 Imports, to name a few. For a long time, it seemed that big-box retailers were facing an inevitable descent into obscurity and irrelevance.”[1] The pandemic appeared to be the final nail in the coffin. As stores were shuttered and e-commerce exploded, consumer behavior changed dramatically.
To the surprise of many, physical stores survived — and some big-box stores, like Target and Walmart, actually thrived. There are several reasons the retail sector survived the pandemic — among those reasons were the adoption of omnichannel strategies and utilization of cognitive technologies (aka artificial intelligence (AI)). As Mandel notes, “Artificial intelligence is enabling big-box retailers to create hybrid physical-digital environments — and that could be just what brick-and-mortar retailers need in order to compete with e-commerce.” It was not always clear that cognitive technologies would find a home in the retail sector. In 2017, Manesh G Pillai, a senior director at SapientRazorfish, openly asked, “Is cognitive computing the future of retail?”[2] Back then, he saw a mixed picture.
He noted that a survey by IBM found that 83% of the retail executives surveyed believed cognitive computing would have a “critical impact” on the future of their organization. At the same time, he observed, “Business leaders are a bit slow to adopt this into their day-to-day businesses. Even in a fast-paced industry like retail, there are more proof-of-concepts than end-to-end business solutions offering cognitive capabilities.” Undoubtedly, the pandemic hastened the implementation of cognitive technologies in the retail sector. Journalist John McCormick (@McCormickJohn) reports a study by International Data Corporation (IDC) found, “Retail is poised to overtake banking as the top spender on artificial intelligence as companies including Home Depot Inc. and Wayfair Inc. turn to the technology for a wider range of operations, from inventory management to more personalized online search and shopping.”[3] In four years, cognitive technologies have advanced from the proof-of-concept stage to implementation. Jeremy King, Pinterest Inc.’s Senior Vice President of engineering, told McCormick, “Everything you can think of in almost every part of retail is being powered by AI.”
Artificial Intelligence in Retail
Ritu Jyoti (@RituJyoti), an IDC group vice president, told McCormick, “Retailers are increasing their AI spending to improve the customer experience and boost sales recommendations amid rising e-commerce activity sparked by the pandemic. … Overall, IDC forecasts global spending on AI will grow from $85.3 billion in 2021 to more than $204 billion in 2025.” Thanks to physical store lockdowns during the pandemic, implementing omnichannel strategies and cognitive technology solutions became imperatives. Below are a few ways retailers are using cognitive technologies to survive and thrive in an omnichannel environment.
• Profit optimization. Mandel notes, “E-commerce sites use pricing optimization techniques to woo customers. They can create special offers to customers who are members, or change prices in a moment to compete with other retailers. Using electronic shelf labels, retailers have much of that ability as well. When connected to an AI-driven pricing optimization tool, retailers can track competitor pricing, and make adjustments at any time. The prices are clearly labeled on the ESLs, and will scan correctly at the checkout lane.” Timing of price changes is critical. No retailer wants to anger a customer who finds a product’s price has changed from the time they put the product in their cart to when they check out at the register.
• Predictive Analytics. Kathryn Deal, Courtney York, and Emily Fuller Opp, attorneys at Akin Gump, note, “The power of data is no surprise in the retail context. Robust data analytics incorporating AI allow companies to bolster customer engagement, manage inventory, predict and reduce churn, and improve targeted promotional activity. Analyzing information about consumers — including browsing patterns, purchase history, movement through the store and product preferences — enables retailers to make informed decisions that can drive revenue and improve consumer satisfaction and loyalty.”[4] Since customer behavior changed dramatically during the pandemic, near-real-time data is essential to keep up with emerging trends. Cognitive solutions, like the Enterra Shopper Marketing and Consumer Insights Intelligence System™, can help ensure retailers are making decisions based on the most recent data.
• Inventory turnover. Mandel observes, “AI tools can track inventory levels, and use that information to help stores turn their inventory over more effectively. Physical grocery stores, for example, can use inventory turnover tools to move items that are nearing their expiration or sell-by dates. Stores can offer discounts on this merchandise, allowing them to sell off the inventory before it goes bad.” Cognitive solutions can also be used to help retailers understand sources of inventory shrinkage and loss. Deal, York, and Opp add, “AI-powered robotic and digital assistance tools are increasingly prevalent in the retail industry. One growing use of those technologies is to increase accuracy and efficiency in supply chain and inventory processes, for example, by using robots to track inventory and provide customers with detailed information about particular products. In addition, digital assistants (e.g., chatbots) using AI allow companies to track and respond to product popularity data, customer questions or dissatisfaction, and shopping activity.
• Trade Promotion Optimization. TPO solutions, like the Enterra Trade Promotion Optimization System™, can help both CPG manufacturers and retailers find the right pricing point for successful campaigns. And, as Mandel explains, AI solutions can also help with clearance item promotions. She writes, “Seasonal merchandise or models that are about to be replaced represent a big challenge to retailers, who often throw everything into a discount bin and try to sell it at large discounts. This eats into profits and weakens the retailer. Using AI, retailers can precisely identify the price where an older item will sell. Rather than practically giving merchandise away, AI helps retailers remain competitive while clearing out unwanted merchandise.”
• Omnichannel Operations. In order to make a sale, retailers must be available when and where consumers are shopping. For most retailers, that means having both a virtual and physical presence. The benefit of a virtual presence is that it makes sales possible 24 hours a day. Mandel explains, “Big-box stores can turn to AI tools to provide their customers with 24/7 availability.”
• Biometrics. The use of in-store cameras to track consumers is controversial. However, Mandel notes, “Computer vision has evolved to the point where it can track individuals as they walk through the store, and identify the items they’ve picked up while shopping. Computer vision enables retailers to operate unmanned stores. The technology can track every item placed in the cart, and integrate with self-checkout machines so that customers can buy whatever they need, any time of day or night.” Deal, York, and Opp add, “Another growing trend in the retail industry is the use of biometrics in AI and XR applications. Retailers are employing facial recognition technology to identify loyal customers in stores so that they can then send personalized communications during their shopping experience. They are also using facial recognition as an asset protection tool to reduce shrink by identifying known shoplifters. In addition, scans of biometric data allow retailers to secure financial transactions and to provide virtual experiences that foster customized and convenient shopping experiences, for example, by creating a virtual experience where individuals can see what make-up products look like on their faces without actually applying any tester products.”
• In-store Product Search. According to Mandel, “Ultra-wideband technology is used to track items indoors, and capable of guiding consumers to within 12 inches of an item. Powered by AI, it can be deployed by retailers in a number of different ways.”
• Employee-Related Uses. Deal, York, and Opp explain, “Retailers’ use of AI and extended reality (XR) increasingly extends to employment practices as well. Retailers are using AI tools to track employee patterns and activity throughout the store to maximize staffing, as well as to improve retail hiring and training practices, by identifying the best candidates in an efficient and data-driven way. XR is being used to train employees in a virtual environment to improve real world customer experience. Finally, many retailers use biometric data to track employee hours and to maintain physically secure locations in a store setting.” It should also be noted that many retailers are having a difficult time finding employees. According to Journalist Morgan Franklin, AI-powered automation could help ease the pain. He notes that the retail sector has been singled-out as one sector where automation is likely to make a big impact on jobs.[5]
Some people may be surprised how quickly cognitive technologies in retail went from the proof-of-concept stage to reality; however, as the 2017 IBM survey found, retail executives had a pretty clear understanding that AI would have a substantial impact on their business. That impact is becoming more significant each and every day.
Footnotes
[1] Pini Mandel, “With AI, Big-Box Stores Can Take On E-Tail Rivals,” SupplyChainBrain, 19 May 2021.
[2] Manesh G Pillai, “Cognitive Computing – Future of Retail?” ET Retail, 10 July 2017.
[3] John McCormick, “Retail Set to Overtake Banking in AI Spending,” The Wall Street Journal, 7 September 2021.
[4] Kathryn Deal, Courtney York, and Emily Fuller Opp, “Retail Artificial Intelligence and Extended Reality: Operational and Legal Trends,” Retail Touchpoints, 30 December 2019.
[5] Morgan Franklin, “How Artificial Intelligence Will Change the Retail Industry,” Datafloq, 31 January 2018.
