Big Data Hits Retailers Big Time

Rado Kotorov's picture
 By | January 13, 2014
January 13, 2014

Some people claim that big data is just a buzzword. Others claim their business fortunes were changed dramatically by the use of big data.

The debate over big data’s value is irrelevant—big data is fact of life. With all the data collection points and data transmitting devices, it’s difficult to reject the advance of the phenomenon. Instead, it’s more insightful to talk about the relevance of big data in retail, and the organizational challenges it presents.

Big data, and how to manage it, confronts every organization with a huge task, but in particular, retailers have a daunting challenge.

In the recent past, a retail megastore could be successful with the variety of products and pricing options that it presented to consumers. Today, real-time big data is creating the “uber” marketplace—that is, offering consumers very relevant choices at any time from any place at the most competitive pricing. The move from simply offering a great selection of choices to offering the best choice at the best time and the best price has forced nearly all retailers to offer universal price matching in order to compete with this “uber” marketplace.

The proliferation of big data is forcing retailers adjust their business practices in these five key areas:

  1. Real-time personalization – participate in real-time customer decision making by offering specific, customized choices at the most opportune times
  2. Predictive analytics – develop proactive, information-based insights into customer actions and decisions to amplify purchasing influence
  3. Micro-targeting – Utilize information to localize customer segmentation and engage customers on their terms
  4. Customer loyalty – create a foundation for self-sustaining customer loyalty
  5. Time to market – accelerate time to market by enabling an agile, flexible supply chain

From an organizational perspective, retailers will also have to refocus in the following ways to leverage big data:

  1. Analytical competencies – For big data analytics to be effective, retailers need to hire and train analytics teams with the skills to deliver on the promise of big data
  2. Data integration – Analyzing big data is only part of a larger, more comprehensive process of data integration required in a fast-moving and constantly shifting world of data
  3. Data quality - Developing downstream automated data quality enforcement ensures accuracy in the decision management process
  4. Data-driven culture - Fostering an interdisciplinary culture where problems are approached from multiple domains – integration, integrity and analytics – with a goal of resolving them quickly but accurately is an ideal environment for maximizing big data
  5. Data distribution – Retailers should incorporate an effective information delivery system that scales beyond information analysts and the C-suite and delivers insights to every employee, partner, supplier, and customer

The retailers who will be winners in this game will drastically enhance both the customer experience and the efficiency of their data operations. Done right, retailers who maximize their big data will earn increasingly larger market share than those that do not.