Most retailers, in order to stay competitive, are mining data to understand what customers want and how to get them to buy more. Walmart, for example, analyzes social media to identify new products. Autozone uses software to change its inventory assortment in a particular store based on the types of cars people in the surrounding area drive.
CVS uses internal data and industry insights to develop new strategies for stocking merchandise and to decide which promotional offers specific customers should receive. For CVS, the first goal of using big data was to identify the best customers. Over the course of data analysis, CVS realized that its best customers were people who frequently visited the pharmacy due to chronic conditions.
CVS also named its hypothetical best customer, Beth. Beth is a 50-year-old woman who takes care of prescriptions for her children, husband, and parents. Once CVS had named its best customer audience, it decided to analyze what else shoppers like Beth purchased. CVS found that in urban stores, customers like Beth, treated CVS like a general store, buying grocery items, snack foods, household items and baby products. In suburban stores, customers were buying more health and beauty products with their prescriptions. Based on these data, CVS developed a new “On the Go” featuring food items and precut fruit, to its urban stores. In its suburban stores, CVS is redesigning store formats to more prominently display health and beauty products.
CVS is also using data to help solve other problems. For example, CVS could never decide if toothpaste and floss should be merchandised next to grooming, first aid, or cosmetics. Purchase data indicated that customers most often bought oral care products along with beauty products; thus, CVS reshuffled its stores to put dental products near beauty aisles.
CVS also found that one-third of its customers stopped taking prescribed medications after a month and half stopped after a year, even though the medicine was meant to be taken for longer. CVS implemented an automated program of texts, e-mails, and phone calls to remind customers to refill prescriptions.
Last year, CVS, through its ExtraCare program, sent 117 million personalized offers to customers primarily via receipt printouts. Through the increased use of big data, CVS now offers coupons to change a customer’s buying habits. For example, if CVS notices a customer typically spends $15.00 per visit, CVS will offer a coupon to drive the sale up to $20.00. In addition, CVS also found that brand-specific offers were redeemed less often. Now, CVS offers category discounts rather than brand specific discounts.
How does CVS use big data to make purchasing and merchandising decisions?
SOURCE: Stephanie Clifford, New York Times, June 19, 2013