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Put Big Data to Work

Traditional retailers generate and capture a wealth of data—most notably, customer transaction histories that can reveal detailed product affinities and promotional and marketing response rates. The emergence of big data and advanced analytical tools means that retailers can capture even greater value from such information, provided they know how to analyze and interpret it. Big data can explain the who, what, when, where, why, and how of retailing.

Although some leading companies have gained a reputation for deft data handling, most retailers have not yet built the analytical capabilities and internal processes necessary to take advantage of the information they can access.

Mastery of big data is important today and will become a critical capability over time. Here are ways retailers can get started with big data:

  • Focus on the most pressing opportunities. Retail companies win by improving sales or margins every day. Management teams should determine how to fuel growth in very specific, targeted ways, rather than trying to build a comprehensive solution.
  • Start with the data you truly need. Sales, costs, promotions, space, store locations, and customer data should be connected—but only to the point that will drive value for the business. Companies will most likely have to connect more data as efforts evolve, but to achieve results quickly, they should limit their efforts to a small subset of available data—the elements they need for individual measures in the near term.
  • Include front-line employees. The people who make daily decisions in retail—buyers, trade planners, and others in similar roles—are hungry for useful information. Companies that include these employees early on will give them a sense of ownership in the process, leading to greater trust in the analysis later on. Ultimately, this will improve the company’s results.
  • Translate the analysis into tangible actions for the broader organization to validate. Ultimately, big data in retailing needs to help people make practical decisions faster and more accurately: Should we promote a product for an extra week? Should we offer a two-for-one deal? Which promotions should we continue and which should we stop? Recommendations should resonate with those making the daily decisions. If people in those roles can’t respond to new information easily, they will ignore it.
  • Maintain trust with consumers. To build trust among consumers and gain access to even greater amounts of personal information for big-data applications, retailers must be transparent about how they use the data and establish the benefits to consumers (such as lower prices and more personalized promotions).
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