With the growing use of technology in recent decades, companies have gained access to a vast amount of information. “Big data” is the new buzzword in multinational corporations all over the world and people who can manage that data are in higher demand than ever before. Analysis of customer purchasing decisions and relevant social media trends gives companies a competitive advantage over their rivals.
Companies can use data in many ways. Netflix, for example, uses piracy statistics to determine which shows are the most sought after by the general consumer. In doing so, they gain insight into which new additions to their streaming collection may net the most attention and profit . Similarly, Amazon uses customer data to simplify customer service calls – they’re able to eliminate the need for stating name, address, etc. and can predict what recent purchases may be giving you trouble . Even Starbucks uses customer habits to select new store locations, leading to the phenomenon of successful locations within mere miles of each other. 
However, when companies go too far in their collection and usage of data, their strategies can backfire. Although most people know that their data is being collected in some manner, few truly care until a company strays into “creepy” territory. In 2012, Target received some flak after sending a high school student coupons for diapers and other baby products. Her father complained that the company was “trying to encourage her to get pregnant” before later realizing that she already was. The father later apologized to Target. It turns out the company used purchasing patterns to maintain a list of customers with a high probability of being pregnant and sent relevant ads in response. This list also contained due dates for each customer estimated through further analysis of purchasing history and information purchased from other companies. 
An analyst from Target responded to customer concerns by saying that they were following all privacy laws, but noted that “even if you’re following the law, you can do things where people get queasy.” In discussing the situation with the pregnant student, he revealed that the company has since revised it’s coupon distribution techniques and now mixes in relevant discounts with irrelevant ones. “We’d put an ad for a lawn mower next to diapers. That way, it looked like all the products were chosen by chance. As long as we don’t spook her, it works.” 
This marks a change in how companies have to use their wealth of information on their customers. Nobody wants Big Brother looking over their purchasing or web browsing habits, especially when it’s a company trying to squeeze out some more profit. Everyone has had the experience of looking at one product on Amazon and having it follow you in advertisements all across the internet – the marketing stops being effective and just becomes downright creepy.
As such, these companies have to be careful in how much they reveal to their customers. Once a corporation is labeled as having disturbing data collection practices, the PR disaster can affect sales heavily.
Aside from data obtained in-house, access to real time analysis of social media can give companies advance warning of developments in virtually any topic. Dataminr, a “leading real-time information discovery company,” capitalizes on this brand new style of corporate analyis. They purport to be able to alert users about breaking news “5 to 10 minutes” before any conventional news source.
In the past, Dataminr has warned stock holders about an upcoming downfall in Apple’s stock prices after finding negative tweets about the company. They also managed to send alerts about the death of Osama Bin Laden nearly half an hour before a single news network caught wind of it. 
Similarly, a company could use the service to warn about potential PR disasters and address them early. As social media has become popular, angry customers have increasingly turned to news outlets and social media to create a viral outrage in the hopes of receiving better service. Especially for the more popular users of social media, a bad review of a product (even made in passing) can be devastating for a company’s public image. The earlier a company can quell these complaints, the better for their public image.
Clearly, big data has great potential for growth in the near future. Imagine being able to pick up on the next big trend in the movie industry or an upcoming fashion fad. Such prediction tools might be a reality in the near future. Engineers at IBM have already developed methods to predict potentially fatal infections in premature babies. They monitor vital signs thousands of times per second to detect any deviations from healthy standards.
This technique is an implementation of “predictive analytics” and it has great potential for corporations all over the globe. Computers are able to pick up on trends to predict huge breakthroughs or disasters where humans simply cannot. If this up-and-coming technology is used along with current analysis tools, it could give companies a “crystal ball” to the near future. Obviously, such a tool would immensely useful, but only time will tell if companies can become the fortune tellers of the modern age.
1. Woollacott, Emma. “Netflix Checks Piracy Stats To Help It Decide What To Buy.” Forbes. Forbes Magazine, 16 Sept. 2013. Web. 18 Nov. 2015. http://www.forbes.com/sites/emmawoollacott/2013/09/16/netflix-checks-piracy-stats-to-help-it-decide-what-to-buy/↩
2. “How Companies Like Amazon Use Big Data To Make You Love Them.” Co.Design., 02 May 2012. Web. 18 Nov. 2015. http://www.fastcodesign.com/1669551/how-companies-like-amazon-use-big-data-to-make-you-love-them↩
3. Thau, Barbara. “How Big Data Helps Chains Like Starbucks Pick Store Locations.” Forbes. Forbes Magazine, 24 Apr. 2014. Web. 18 Nov. 2015. http://www.forbes.com/sites/barbarathau/2014/04/24/how-big-data-helps-retailers-like-starbucks-pick-store-locations-an-unsung-key-to-retail-success/↩
4. Duhigg, Charles. “How Companies Learn Your Secrets.” The New York Times. The New York Times, 18 Feb. 2012. Web. 18 Nov. 2015. http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html↩
5. Hill, Kashmir. “How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did.” Forbes. Forbes Magazine, 16 Feb. 2012. Web. 18 Nov. 2015. http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/↩
6. “Mining for Tweets of Gold.” The Economist. The Economist Newspaper, 07 June 2014. Web. 18 Nov. 2015. http://www.economist.com/news/business/21603468-startup-finding-valuable-information-twittersphere-mining-tweets-gold/↩
7. “Big Data Success Stories.” IBM. IBM, n.d. Web. 18 Nov. 2015. ftp://ftp.software.ibm.com/software/data/sw-library/big-data/ibm-big-data-success.pdf↩