| | AUGUST 20198CIOReviewIN MYOPINIONThe arrival of Big Data and the ability to process it have led to improvements in machine learning, creating new use cases for this technology. As a result, machine learning, algorithms that execute tasks without preprogrammed rules, has become a crucial part of a retailer's operations. Some of the most important use cases include better personalization, lowering operational costs and enabling the future of commerce. It will be important for retailers in 2018 to determine how to deploy this technology to drive revenues and lower costs.Improving the Customer Experience through PersonalizationOne of the first applications of machine learning was for product recommendations. The improvement in machine learning means that not only have the recommendations become better, but other types of personalization are possible. Many retailers offer personalized search results to shoppers based on their past purchase history and other behavior. eBay has personalized its home page for shoppers with the aim of reducing the time it takes to find an item.Another area of personalization is price optimization. Groupon Goods uses the Boomerang Commerce Price Platform management tool to optimize its prices. Groupon looks at external factors, such as consumer demand and market elasticity, and at internal factors, such as traffic and sell through targets, to optimize its prices for shoppers.Decreasing Operational CostsMachine learning is tackling tough operational challenges to lower costs. One of the best use cases is for inventory management and forecasting. Machine learning programs can make predictions on the optimal amount of inventory to avoid out of stocks or too much inventory. This helps retailers avoid lost sales and markdowns. Another area where machine learning is cutting costs is with the aim of reducing apparel returns. About 30 percent of online apparel purchases are returned. Not all of the merchandise can be resold at full price and the remainder makes its way through an expensive liquidation process. Retailers are turning to machine learning to help shoppers better understand the fit WHO RUNS RETAIL? THE MACHINESBy Michelle Grant, Head of Retailing, Euromonitor InternationalMichelle Grant
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