Artificial Intelligence in Brick and Mortar Retail
Source: Goulston & Storrs
Headlines about brick and mortar retail tend to be dominated by how these establishments are in decline while online retail is burgeoning. Fortunately for brick and mortar retailers, their demise is not preordained since tools from the online retail universe may also help them succeed. One such tool is artificial intelligence (AI), which is expected to grow rapidly in the next few years.
Online retail is able to target customers easily because of the large data collection that occurs with every transaction. However, brick and mortar retail establishments may employ various AI tools to collect data to tailor in-store shopping experiences and target consumers. For example, video and/or audio surveillance can be used to track shopper activity in stores, and stores can then predict customer preferences and behaviors by analyzing and conglomerating in-store surveillance. Such surveillance methods can use facial and/or voice recognition software to analyze facial and voice expressions to understand how customers react to particular products or experiences.
Robots are another AI tool that may help brick and mortar retail compete more effectively with online retail. Robots may enhance the physical shopping experience in many ways. Humanoid robots can be deployed into retail establishments to greet customers, answer questions, and guide them through the store. Lowe’s has piloted a robot program at its Bay Area stores, where robots help customers search for products and guide them in the stores. Also, robots are being used and expanded to check and resupply inventory, deliver products, and assist with checkout and payment.
Finally, the collection of sales data can help retailers personalize a customer experience and ultimately help increase sales – whether in-store or online. Data can be collected online and then used in stores, or data collected from a customer’s previous visit can be used to enhance his or her next visit to a bricks and mortar store. “Machine learning” can discover patterns in a customer’s behavior and then make suggestions or produce incentives, such as instantly printing coupons for products that are likely to be desirable to an individual customer. The same data collection can be used to better tailor inventory, customize shopping experiences, adjust pricing, and refine product selection. While all of these techniques are equally useful online retail tools, their utility in the bricks and mortar environment may help these physical establishments remain competitive with their online counterparts.
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