Beyond Black Friday: Reimagining Retail With AI

The holiday shopping season kickoff isn’t called “Black Friday” because of the chaos in stores when shoppers turn up in droves. The origin of the name goes back to the bookkeeping color code — retailers make their profits in the last quarter of the year, hoping to finish “in the black.” But profitability is a mixed bag for retailers lately, with talk of a “retail apocalypse,” even while consumer spending remains strong.

As the National Retail Federation points out, retail is growing. Online sales account for only about 10 percent of total retail sales, and most retailers sell in-stores as well as online. The trouble in the retail sector is about shuttered stores’ failure to keep up with changing consumer expectations. The flip side to that is an opportunity to reimagine retail, and the sector’s good news stories show that artificial intelligence (AI) is the key to success.

How AI Can Move Retail From Red to Black

This year, the window for moving from red to black is shorter since there are fewer days between Thanksgiving and Christmas. Retailers that incorporate AI into their decision making will be well-positioned to make the most of the shorter timeline because AI can optimize every aspect of the business, from the customer experience to the supply chain to marketing, sales and operations.

Retailers typically have a long supply chain lead time since many decisions are already made by the time the busy season arrives. However, AI allows retailers to pick up on “soft signals” in the data and determine which are real and which are merely noise. AI’s insights allow retailers to identify emerging trends sooner and adjust merchandising, product mixes, customer experience, etc., more quickly to maximize sales.

Another advantage of putting AI to work in the retail environment is that it allows retailers to address the complexity of the modern customer journey. Today, a customer might make first contact a retailer online, then visit one of its stores, before ultimately purchasing online — or vice versa. AI allows the retailer to create a hyperpersonalized experience, recommending specific actions tailored for each stage of the customer journey.

Returns are a huge expense for retailers, costing them up to 20 percent of their total sales. The primary reason people return merchandise is that the item didn’t fit. Retailers can’t rely on supplier consistency to solve the problem, but AI can analyze buyer behavior and identify which sizes and styles fit the shopper. With this technique, retailers can reduce their return rate significantly while improving customer satisfaction at the same time.

Using machine learning and AI together can also help retailers optimize store types to serve local demographics. Many retail chains have six or seven types of stores. With AI, they can potentially have hundreds of types, creating a unique product mix for each. AI can also power the back-end infrastructure to support the strategy, funneling specific goods to stores where those items are selling quickly.

Small vs. Large, Risk vs. Reward

One cause of the “retail apocalypse” is that large chains tend to be risk averse. Acting prudently makes sense up to a point, but as the Amazons of the world were out there changing everything — including the expectations of an entire generation of consumers — some retailers were too slow to respond. And when they did try to adjust, it was too little, too late. Others embraced the new possibilities.

Scrappy startups like personal styling service Stitch Fix took a transformative risk. The company and similar businesses combined the human touch with data and analytics to drive recommendations and create an experience tailor-made for digital natives. There’s a lesson in Stitch Fix's story for other retailers, and it applies beyond Black Friday: reimagining retail with AI entails risk, but the rewards can be huge.

Dr. Anil Kaul is the co-founder and CEO of Absolutdata, a company specializing in big data analytics, marketing analytics and customer analytics.