Big Data at Macys.com
Macys.com is considered the equivalent of a single store at the giant retailer’s structure, but it’s growing at a 50% annual rate—faster than any other part of the business. The division’s management is very oriented to and knowledgeable about IT, data, and analytical decisions. Like other online retailers, Macys.com is heavily focused on customer-oriented analytical applications involving personalization, ad and email targeting, and search engine optimization. Within the Macys.com analytics organization, the “Customer Insights” group addresses these issues, but it also has a “Business Insights” group (focused primarily on supporting and measuring activity around the marketing calendar) and a “Data Science” organization. The latter addresses more leading-edge quantitative techniques involving data mining, marketing, and experimental design.
Macys.com utilizes a variety of leading-edge technologies for big data, most of which are not used elsewhere within the company. They include open-source tools like Hadoop, R, and Impala, as well as purchased software such as SAS, IBM DB2, Vertica, and Tableau. Analytical initiatives are increasingly a blend of traditional data management and analytics technologies, and emerging big data tools. The analytics group employs a combination of machine learning approaches and traditional hypothesis-based statistics.
Kerem Tomak, who heads the analytics organization at Macys.com, argues that it’s important not to pursue big data technology for its own sake. “We are very ROI-driven, and we only invest in a technology if it solves a business problem for us,” he noted. Over time there will be increasing integration between Macys.com and the rest of Macy’s systems and data on customers, since Tomak and his colleagues believe that an omnichannel approach to customer relationships is the right direction for the future.
Source: Big Data in Big Companies, Thomas H. Davenport and Jill Dyché, May 2013 (Go to Suggested Readings to view full article)
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