Mining the Mind

            As a technologically dependent society, not a day goes by where we are not bombarded with an endless barrage of glitzy advertisements and subtle encouragements to look, spend, live, and love in a carefully constructed manner. While sales and marketing have focused on many of these techniques since the beginning of time, within the past three decades, a relatively new process called data mining, has been working behind the scenes, changing the commonly understood foundation of social marketing forever. While there are many consumer-oriented companies that have recently implemented the use of data mining, the Wal-Mart Corporation has been pioneering this technology since its inception.

           In fact, Wal-Mart uses data mining to determine how the relationship between internal factors, which are the activities occurring within the company, like how the placement of candy in food stores is often conveniently located at the visual level of a child, and external factors, which are typically trends that reach beyond a company’s control. One example that comes to mind is the recall of an extremely popular child toy. Although the company may not be directly responsible for the toy itself, they can harvest the information collected from data mining warehouses to promote a new toy that is a safer alternative. By analyzing the correlation between the internal and external aspects of the company, analysts can then determine the projected impact on sales, consumer satisfaction, and ultimately the profits of a corporation.

            Over the past few years, the process of data mining has “become [the] well-established discipline within the domain of artificial intelligence and knowledge engineering (Data Mining: Past, Present, and Future)” that analyzes statistics from different perspectives of a company and condenses it into information which, then aids businesses in making informed decisions that can increase revenue and cut costs. As touched upon briefly above, data mining sifts through “historical data, such as customer response [with regard to] demographic, geographic, sales and history ("Data Mining: What Is Data Mining?"),” which in turn, can successfully “target the right audience, increase return on invested marketing money, [and become more familiar] with the purchasing behaviors of consumers ("Data Mining: What Is Data Mining?").” Basically the concept of “data mining” can be broken own into four different categories: classes, clusters, sequential patterns, and associations. While all these methods are implemented by an array of companies and businesses, in order to gain a greater understanding of how data mining is intertwined in each of our lives, this paper will focus on the “association” classification and how this particular method helps Wal-Mart infiltrate the minds of their consumers. 

            About a year ago in a marketing course, a professor pointed out a startling correlation between the location of beer and diapers in the supermarket. According to this professor, a “popular Mid-western grocery chain decided to utilize the data mining capacity of Oracle software to analyze local buying powers ("Data Mining: What Is Data Mining?").” Interestingly enough, results discovered “that when men bought diapers on Thursdays and Saturdays, they also tended to buy beer ("Data Mining: What Is Data Mining?").” Bared with this new knowledge, “the grocery chain decided to not only move the beer display closer to the diapers, but also make certain that the beers and diapers were sold at full price on Thursdays and Saturdays ("Data Mining: What Is Data Mining?").”

           After hearing this story, my professor encouraged the class to try and research the actual marketing concept implemented by the grocery chain in this particular example, and come to the next class with more information and examples of how this
process effects our lives each and everyday. Needless to say, after a little research, the answer appeared on the screen—data mining. As I read on, it became clearer to me that this concept was not simply a tool used by stores to help them uncover a more logistical product and store layout, but a tool that could, in essence, penetrate the minds of consumers, and navigate those buyers towards any particular area they showed any interest in. It turns out that everyday; our Internet searches and purchases (both online and in-store) yield topics of particular interest. Companies then filter through this obtained knowledge and project subliminal ads (both online and paper), emails, and side bar pop-ups that resonate in the consumer brain and theoretically lure buyers back into the store or site to make that purchase. However, throughout my research, it became clear that Wal-Mart had been a key player in the application of this innovative knowledge.

            The $100 billion data mining industry, which is growing at a pace of 10% each year (“Data Mining Pushes Marketing to a New Level”) undoubtedly influences a whole host of business operations throughout the world, with respect to Wal-Mart, this process not only impacts in-store operations, but also warehousing and online ventures as well. According to UCLA professor Jason Frand, “Wal-Mart captures point of sale transactions from [every single one] of their stores in all 15 countries in which they are located ("Data Mining: What Is Data Mining?").” This data is then “transmitted to a massive 583 terabyte data warehouse ("Data Mining: What Is Data Mining?").” From this point, Wal-Mart then allows most of their suppliers to have access to the data collected on that particular company’s product(s). Suppliers than use this data to identify customer buying patterns at the store display level ("Data Mining: What Is Data Mining?").

           In recent years, many companies such as Wal-Mart have introduced customer loyalty cards. While these cards offer many perks to consumers, Wal-Mart actually uses the “data from this card system to more closely monitor consumer purchases, providing Wal-Mart with more accurate demographic data of customers, like where, when, andwhat customers actually bought ("Data Mining: What Is Data Mining?").” By using this more individualized purchase history, Wal-Mart can “develop products and promotions to appeal to specific customer segments ("Data Mining: What Is Data Mining?")” which in turn, increases sales, profits, and overall customer satisfaction. Customer satisfaction is a major component of every successful business. Most individuals feel a sense of loyalty to a company who seemingly takes the time out to acknowledge the important events of one’s life, whether that is something as common as a birthday coupon, or gift ideas for your upcoming wedding. In theory, data mining helps establish this loyal relationship with consumers that will only perpetuate the reputation and growth of any company.

            When analyzing the concept of data mining by itself, it is easy to get lost in the technicalities of how this process actually works. However, it is important to recognize the correlation between data mining and social media marketing. In essence, they both work to bring both convenience to the customer and promote sales for the company through the identification of a defined target market. For example, if a Wal-Mart store in Vermont recognized an influx in the purchase or online inquiry of snow boots for the upcoming winter, the company would likely reorganize the layout of the store to make locating the actual boots easier to find, as well as offer coupons and ads via email, Facebook, and/or Twitter to attract the largest segment of buyers and ultimately promote and generate sales for the corporation. Despite the fact that both data mining and social media marketing are so closely related, the two concepts do differ. Unlike data mining, which focuses on investigating consumer behavior by analyzing consumer preferences and buying habits by mining “massive sets of quantitative data and applying complex algorithms to uncover patterns ("Examples Of Data Mining Vs. Traditional Marketing Research"),” social media marketing offers a more direct approach by applying the knowledge obtained by outside research and finding ways to appeal to consumers. Another difference worth noting is the idea that data mining is primarily rooted in the analysis of past data, where are social media marketing is more geared towards affecting the future behaviors of consumers.

            While both data mining and social media marketing are two separate and comprehensive topics apart from one another, each innovation enhances the other, particularly with regard to consumer based retail businesses. While it is true that the concept of marketing has likely been around since a means of communication was first developed, now that our society has become so reliant upon technology, data mining seems to broaden the material and knowledge needed for social media marketers to better understand and connect with the consumer. However, it is worth noting that without social media marketing, it would very difficult to interpret data mining results and apply the material in a comprehensive manner. Thus, social media marketing is necessary to help “translate” data mining facts into something that a company can actually put to use. By combining these two methods together, each of these innovations benefits both business and society as a whole. In fact, back in “1991, Wal-Mart pioneered the technological research craze and investeted $4 billion to create RetailLink ("Facebook, Wal-Mart Relationship Could Rely on Big Data."),” Wal-Mart’s original database system. This initial investment is even more startling when compared to how much Wal-Mart spends on their advertising budget. Apparently, in 2010, Wal-Mart only spent $2.5 billion of their massive $418.9 billion yearly revenue on marketing. This total also includes efforts to penetrate consumer audiences through social media marketing ("Do You Pay Enough For Advertising? One Big Corporation Spent A Jaw-Dropping $4.2 Billion Last Year.").

Without accurate research, companies would have a difficult time projecting the wants and needs of customers in a way that maximizes the overall wealth of a company. Living in this technologically obsessed world, it is clear that the marketing element of a business needs to grow and change with the increasing expectations of the consumer. By appealing to the lifestyles of customers in ways that capture their attention, whether that is through the Internet, mailings, television, pop-up ads, etc. companies will continue to flourish in society.

            Although data mining is a newer conept, the means by which companies gather necessary information is always evolving in new and more advanced ways. For example, Wal-Mart developed a think tank group, WalmartLabs, to derive a new method of capturing more consumer information. According to Jennifer Van Grove of Venture Beat
Blog, Wal-Mart has created a new app that mines the Facebook data of its users to help you buy better gifts. This app is called Shopycat and is specifically designed to help shoppers with both holiday and everyday shopping occasions (“Wal-mart’s new Facebook app”). “This program takes a person’s likes, status updates, and declared interests, and ties them to a vast product catalog of Wal-Mart and financial partners, Barnes and Noble, NBC Universal, and Red Envelope (“Wal-mart’s new Facebook app”).” If this app proves to be as successful as it is creators’ hope it will be, “Shopycat has the potential to infiltrate Facebook’s 800 million user members (“Wal-mart’s new Facebook app”).”

            It is clear that the future of data mining will only improve as new “data mining techniques are being embraced by research and development and other information-rich companies whereby such services can be used for furthering the growth and interests of the respective companies ("Data Mining Future Trends Predicted for 2012 and Beyond.").” Within the next few years, data mining companies are working to access data information found in “memos, emails, notes, online chats, presentations, and texting through semantic (also known as image modeling) mining that will be able to uncover pertinent information through hidden meanings in personal data and documents ("Data Mining Future Trends Predicted for 2012 and Beyond.").”  However, with every major positive innovation, there are always concerns and uncertainties. Although data mining is an extremely successful resource for businesses, many consumers feel that this process is an unauthorized invasion of privacy. One man, Robert Cole, of Ferguson, Mo., recently filed a complaint with the Privacy Rights Clearinghouse in San Diego to comment on what he felt was an infringement of his privacy. According to Cole, within days of researching diabetes for a friend on his computer, he began receiving coupons and informational packets on the disease. Cole, who does not suffer from this disease, found it appalling to think that someone can be classified under a particular category without even giving out any information ("Data Mining Spurs Users to Protect Privacy Online"). Unfortunately, he is not alone. Many people have begun to catch onto the infringement data mining has upon ones personal and seemingly private research and information. In recent years many consumers have begun to suggest that personal data recovery should have legal implications. Some privacy advocates believe that consumers should be given various levels of “opt-out” choices with regard to the release of personal information. Some of these choices include: no data mining allowed, for internal use only, or information being given is for both internal and external uses.

            Throughout history there have been many innovations that were believed change everything as it was once known. While many of these innovations were fleeting moments of glory that faded into the background, others continue to flourish and inspire greatness in times of change. Data mining is no different. This process will grow and adapt to the ever-shifting phases of life, and social media marketing, as we know it today. Just take a minute and think about the realm of possibilities that could result from data mining! One thought that scares me the most is the possibility of creating a computer, or some sort of technological device, that can read my mind and sift through the data to obtain the results the program needs. While this might be a convenient invention when we wanted to record our thoughts into an essay, for example, but in retrospect, it could potentially become a total invasion of privacy. However, while there are many possible directions data mining can branch out into, one thing is definitely clear, it will not only prove to stand the test of time, but continuously evolve and enrich the business community for centuries to come.