Upon dropping in to your favorite trendy clothing store, you come across a shirt depicting Kanye West (your best friend’s favorite artist) that would make the perfect gift for her upcoming birthday. Although you could never put a price on your friendship, the shirt at the price listed in the store is slightly out of your comfort zone, so you decide to do a quick search on your smartphone and come across the mobile site of a “trendy clothing wholesaler” who is selling the shirt at a price that suits your budget a bit better. When you return home, you decide to search the store’s sight on your computer to make the purchase. No sooner do you type “K” than the exact shirt you’re looking for appears in the search bar. After you select the shirt, the site recommends that you also check out a shirt that just so happens to depict your own favorite band “Little Dragon,” causing you to pinch yourself while peering over your shoulder to make sure you aren’t dreaming/being stalked. Upon regaining your senses you decide that the “Little Dragon” shirt is one of the coolest things you’ve ever seen, and you end up buying both.
Your first inclination might have been to think “how did they do this?” before quickly passing it off as pure coincidence. But in actuality from the very moment you searched for the Kanye West shirt in the trendy clothing store you were already setting yourself up to buy both shirts. This is just one example of how so-called “Big Data” enables those who know how to harness it to unlock its enormous potential. The term “Big Data” is used to refer to datasets so large and complex that it becomes difficult to process using traditional on-hand database management tools. Without ever having logged into the clothing wholesaler’s website on your phone computer, Big Data was being used to create a profile of you as a certain type of buyer through a combination of processes known as cross-device retargeting, predictive search, visual browsing, and a few others.
In short, by using the plethora of signals made available by Big Data, including browsing patterns and network locations, cross-device retargeting allows businesses to know if a web and a mobile user are the same person without requiring them to log in. In the above example, this method made use of the fact that the networks on which you searched the mobile site and regular site were close to one another. Using this information, it was able to “predict” that you were looking for the Kanye West shirt as soon as you typed a K. Finally, using the visual browsing technique pioneered by sites like Amazon, the site made use of Big Data to suggest that you also look at the “Little Dragon” shirt.
The potential growth for Big Data analytics is tremendous and will prove extremely beneficial to companies that choose to embrace it. A study by the McKinsey Global Institute labels Big Data as the next frontier for innovation, competition, and productivity across many industries, particularly retail. According to the study, retailers have seen their operating margin increase by more than 60 percent after utilizing Big Data. Clearly, there is big value to be found in Big Data.
The research identifies several ways in which using Big Data creates value:
First, Big Data analytics filters information. It makes information transparent that otherwise would have been smothered by vast amounts of data. Second, it can improve retail efficiency. Trends can be observed such as those in inventory as well as employee and management behavior. Third, it grants you the ability to better tailor to individual customers. Using Big Data allows you to more narrowly segment customer interests and therefore better concentrate service, offers and deals according to their tastes. Lastly, Big Data can be used to improve after-sales processes. Sensors embedded in products can be used to obtain customer information and better cater after-sales services as well as future product development. This is particularly lucrative for the auto industry in which after-sales service is a significant source of revenue for dealerships.
While the fact that the wholesale clothing site was able to correctly guess your favorite band from “knowing” your friend’s is somewhat of an exaggeration, it exemplifies the potential that Big Data possesses. Perhaps one day soon the use Big Data will be so advanced as to be able to draw connections between music taste and likelihood of friendship. In any event, big things are happening with Big Data...