What Does Big Data Mean For Retail?

  • May 9, 2014 at 12:13 PM EDT
  • By Retail TouchPoints Team
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By Harbinder Khera, CEO, MindMatrix


Discussions of Big Data are everywhere in the news media. Frequent articles appear in mainstream newspapers and magazines discussing the extraordinary growth in the data being collected from consumers at all different touch points, and much of it has to do with individual privacy. But what is the meaning of Big Data for the retail industry? Does it present any threats and opportunities for this critical sector? In today’s blog we’ll be looking at the impact of Big Data on retail.

Properly designed analytics using Big Data offer retail vendors a range of tools to increase sales and improve the customer experience. In this blog, we’ll define Big Data, where it comes from, and then look at the different ways it can be used to drive sales as well as create consistently more effective customer interactions on every sales channel.


First, what is Big Data? Big Data is nothing more than the term that labels the flood of data that is collected from all the new (and old) sales channels where customers interact with vendors. The reason Big Data become a hot topic is that we now have the ability to collect and store far more information than ever before. For example, POS systems collect data about who bought what, when, in what color and size, and what store location. (Did you know that most popular colors for cars vary from city to city in the U.S.?) Anyone who has bought groceries knows that the POS terminal identifies the purchase and provides coupons that are relevant to that individual buyer. (A dog food purchase yields a coupon for dog treats.)

There are many other wells of information available. One source of data similar to the POS, but providing far more personalized information is the online transaction. Another newer and very rich source of data includes the likes, follows, and postings made on social media sites. Loyalty programs connect consumer IDs to individual purchases and identify buying patterns.

Anyone who has been on Amazon is aware of what can be done with the data yielded by tracking browsing patterns. Finally, there are additional sources of Big Data that are still in development. Of particular interest are new tools using mobile GPS to identify a consumer’s location and behavior in a brick and mortar location. This particular source is being pursued warily due to privacy concerns. Together, all of these comprise the primary sources of Big Data available to retail.

With this understanding of the sources of Big Data, it may be valuable to look at what threats the retail industry as a whole has been facing in the last few years.

 First, of course, is the recession that began in 2008, and which still represents a formidable barrier to revenue development in all sectors of retail. The recovery has been slow, especially in the area of job growth, which translates into less spending. The continued low rate of inflation also doesn’t encourage spending, since consumers know the item they want today will be available at the same price in the near future. Perhaps more serious than the effects of the Great Recession, however, are the long-term implications of the Internet on the retail sector, especially the brick and mortar segment.

First, we have the effect of the endless knowledge available on the Internet. Consumers now face almost no limitations on their ability to make full and deeply informed decisions. This ability has been enhanced with the arrival of mobile and tablet devices, which can be used anywhere, anytime.  This has also led to the rise of the ultimate retail nightmare called “showrooming,” where consumers go to brick and mortar locations to get hands-on exposure to a product, then go online to find the cheapest available online vendor.

And of course, social media represents its own challenge. Where an irritated consumer might have complained about a service or product problem to a few friends, now it can be immediately broadcast on Facebook or Twitter and read by an unlimited audience. Carefully researched and ranked products evaluations by respected organizations such as “Consumer Reports” now exist side-by-side with mass posting sites like Yelp.  In short, the rise of the Internet has raised new and significant threats to the retail sector.

Despite these threats, we believe that, in balance, retail will benefit from the arrival of Big Data. When properly analyzed and used, Big Data can serve to address the threats listed above, and then move retail further along to provide greater levels of effective customer interaction.  

There are significant areas where Big Data can be used to help sales. Macy’s argues it saw a one year increase of 10% in store sales through the effective analysis of the data collected through all of its touch points. Kohl’s and others are looking at the possibility of tracking customer location in-store to send coupons or promotions related to the department where a consumer is spending most of their time. Dawdle in winter coats and get a mobile coupon for wool or fleece overcoats.

Let’s look at just a few specific examples where Big Data can help turn threats into opportunities.

Consider the issue of the in-store shopper. How can Big Data both sidestep the risk of “showrooming,” and help improve the store’s interaction with that customer? With online apps, stores will be able to track the location of a consumer in the store, and identify where she may be spending most of her time. With that information, a promotion might be sent for nearby products. More sophisticated technology could also push specific customer data to a salesperson on the floor. Using purchasing data, the salesperson can recommend items as if he has a long history serving that customer. Also, effective, friendly in-person interaction can cut the chances of “showroom” purchasing.

Social media has developed as a new area to develop more effective customer relations. Hotels, in particular, have learned to use Big Data to meet or exceed customer expectations, tracking preferences in room location or types of pillows. By building a database of a customer’s likes, hotel chains can develop strong brand loyalty. Frequent travelers can be assured their expectations are known and met.

Another area where hotel chains have learned to improve customer relations is social media. Hotels now track tweets and Facebook postings expressing dissatisfaction. A traveler who tweets that the room he just got is on the noisy front street might get a phone call within a few minutes from the front desk offering a change to a quieter room. That traveler is not only happier, he is very likely to post a follow-up bragging about the quick response.

In summary, there is no end to the examples of where and how retail can use information to offer greater value. The circumstances for using this to serve customers are limited only by imagination. Big Data is providing personal customer-specific information that allows a retailer to respond directly, and in real-time, to consumer needs and interests. Technology provides understanding. Retailers willing to spend the time to analyze data will be ahead of everyone in providing greater customer value. The takeaway is that the opportunities presented by Big Data far outweigh the threats posed by the growth in consumer awareness and knowledge.


Harbinder Khera brings expertise in sales and marketing. He also provided IT consulting services to Southwest Airlines, Nationwide Insurance, IBM, Siemens, Citibank, and Sprint PCS. Harbinder has an MS in Information Networking from Carnegie Mellon University (CMU), and an MS in Computer Engineering from Florida Atlantic University. He has published numerous articles in the IEEE conference proceedings and has presented in various trade shows in the field of wireless and high-speed networks. He is a member of Phi Kappa Phi honor society and a member of the Dean’s Leadership Council at CMU.



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