Big Data Shopping Big data is a relatively recent concept in the marketing world, that describes the process of analyzing massive data sets to unearth trends. The data sets are so large that it would be almost impossible to find such trends without high-powered analytical technology. Big data has been facilitated by the ability to gather massive amounts of information about consumer profiles and shopping trends. The primarily facilitators of big data collection are credit card companies and online companies like Google and Facebook that track people's purchasing and computer usage patterns. Big data has been used in a lot of different industries to revolutionize everything from health care to manufacturing to government (Manyika, et al., 2011). Retailers use big data to better understand the "path to purchase" and then adapt their strategies to take advantage of this keener understanding (Macy, 2013). Some retailers have found that the use of big data can increase operating margin by upwards of 60% (Manyika, et al., 2011). This occurs because retailers are able to better forecast demand for specific types of products and then are better able to sell those products by guiding the consumers through their path to purchase. This paper will analyze the use of big data by retailers, as they adjust to this new technique and find ways to apply it to their businesses.

How Big Data Works

Most marketers are enticed by the promise of big data, but using it effectively is a challenge. Many marketers are still trying to come to grips with the best applications for big data technology. In order to maximize the gains from big data, marketers need to understand how it works. In general, big data begins with gathering the data. Data sets are gathered by companies that have access to individual transactions and then compile this data. At Google, searches are the transactions, while at credit card companies it is actual sales. Big data essentially works like a loyalty program, but on a much larger scale. The data gathered will include several variables, and millions of consumers. Then, trends are determined and identified through the processing of the data through applications that specialize in big data. Companies have the ability to gather their own data, but in many other cases they buy it -- this depends on the business. The more the company knows, the more it can understand about the path to purchase. Retailers seek to understand the data, for example in order to know what products will be sold when. A basic decision without big data, for example, would inform a retailer that spring clothes should go on sale by February because people want to buy new spring clothes the minute the first hint of spring comes into the air. However, big data will be able to break that down in a much more refined way so that the company will know who will buy what and when. Correlations be made that will help put the retailer right in the mind of the consumer.

Online retailers are able to gather better information that will allow them to help themselves. For the holiday season, online retailers will have data from past holiday seasons that they can use in the design of their website in order to increase sales. These can be matched against other variables as well. So the processor would determine, as an example, that when the temperature drops below 30 in Minneapolis that sales of hockey sticks increased 20%. An online retailer can take that data and when a Minnesota IP comes into their store, they can offer a deal on hockey sticks or an enticement to offer higher margin related items like skates. Wal-Mart has taken this approach, for example, ensuring that snowblowers or things like that are front and center as soon as there is a forecast for snow. Big data can actually do this on a very refined level, allowing for adjustments on a per-customer basis. So the recommendation that is offered to me is different from the recommendation that is offered to somebody else. The data might know that people in a certain zip never buy snowblowers or lawnmowers, and conclude that zip is mostly apartments, and instead offer something else. Big data is about selling the right things to the right people at the right times. Such website enhancements are critical to the success of big data (Hockenson, 2013).

Many retailers have found considerable success using big data techniques. A study in eMarketer (2013) notes that 85% of companies that had used big data had already made changes to their marketing programs that revealed increased sales, sign-ups, registrations, ROI, customer satisfaction and sales leads. Things like sign-ups will contribute...

Understanding the customer across multiple media types is an important characteristic of big data, because the information gathering platform is often something like Google -- where one signs in on a Google account across the Internet, their Android device and Chrome browser -- or their credit cards, which are used across platforms. Furthermore, big data often gives companies the opportunity to get feedback from consumers, and this feedback is often rapid and of better quality than would otherwise be available without the big data techniques.
That consumers also report increased satisfaction is one of the most interesting things about big data. Companies want to learn more about consumers to guide them down the pathway to purchase, but the consumers also benefit in that their purchasing decisions are made more efficient. When you visit Amazon and it offers recommendations based on past browsing, this saves the consumer the time it would otherwise take a search for such information. Thus, when the company makes the shopping experience smoother, everybody benefits. Consumers appreciate having to make fewer clicks to find and purchase what they want. Thus, big data in many respects is a win-win situation for retailers. In a retail store environment, this can be reflected in the store offering a deal to the customer based on purchase history. So instead of offering a deal on something the consumer does not even want, the store offers a deal on something the consumer does want. This benefits the consumer, and the store, because they both get something.

What big data does it that it reduces information asymmetry between consumers and retailers, bringing the interaction between the two closer to the condition of economic efficiency. Consumers often have trouble communicating what they want to business, and big data helps to resolve that problem. A good example would be a situation where in the past a consumer would have to talk to a salesperson in the store and then the salesperson might take that information and make a recommendation. The more experienced a sales person is, maybe the better the recommendation will be. Big data allows companies to do this without relying on a drawn-out process of getting to know the consumer directly, and without employing thousands of expert sales people. Big data would theoretically allow the company to make the same quality recommendation simply based on analytics and advanced customer profiling from its vast data sets.

The Future of Big Data in Retailing

Both the McKinsey study and the eMarketer study noted that while the benefits of big data are being reaped by many companies, few companies truly believe that they have maximized their use of big data or tapped its full potential for effectiveness. Companies are just beginning to realize the potential of big data, and this is something that bodes well for the future. Retailers both online and offline are going to utilize big data more comprehensively and more effectively in the future than they do today. Only 29% of businesses have reported that they have revamped the way they do business in order to accommodate big data (eMarketer, 2013). The time will come, however, when companies re-envision how they want to run their businesses, to fully capture the results of having big data at their fingertips.

Conclusion

Big data offers tremendous potential for retailers, and many are only now just beginning to realize the potential of the refined information that is available from very large data sets. Online retailers have benefitted significantly to this point, but offline retailers are starting to understand their power as well. Big data is used to get to know the customers better, in particular the pathway to the sale. With this knowledge, retailers are better able to target their offerings and they are better able to guide consumers down the pathway to purchase. Consumer also report benefits from big data, because it makes their shopping experience much smoother as well. The future of big data is massive, because companies currently using it are reporting increase in profits, yet many are convinced they have not yet approached the true potential that big data techniques have to offer.

References

eMarketer. (2013) Big data helps reveal consumer behavior. eMarketer.com. Retrieved December 11, 2013 from http://www.emarketer.com/Article/Big-Data-Helps-Reveal-Consumer-Behavior/1010357

eMarketer. (2013). What do marketers want from big data? eMarketer.com. Retrieved December 11, 2013…