How Data Science Will Change the Marketing World as We Know It
Big Data. It’s one of those terms that is now so widely—and, let’s be honest, indiscriminately—used in the business world that even the least cynical among us are probably getting sick of it. It seems to get thrown around to fill gaps in waning meetings and to make businesspeople sound like they’re up with the digital times.
But the thing about “Big Data” is that although it might be overused—and occasionally misused—it isn’t a meaningless cliché. Digital technology has swept away the analog world we once worked within and inundated us with data. And the more sophisticated the digital technology gets, the easier it makes it for us to send information or for others to track our buying habits. In other words, more and more data is generated.
It’s an often-repeated statistic: In 2013 IBM claimed that “90% of the data in the world today has been created in the last two years.” More recently, in 2015, Cisco predicted that the amount of data created in 2019 will eclipse the total data created in all prior Internet years combined. And, within two years, each person will apparently be producing, on average, 1.7 megabytes of data every second.
Big Data is… well… that: an enormous amount of information. Specifically, information that can be collected and analyzed (which is a generally accepted broad definition of data).
But is there a more precise meaning? And what are the implications for marketing?
“Big Data” really began its rise to prominence in the early 2010s, but it was, according to a word sleuth from the New York Times, being used in Silicon Valley as far back as the 1990s.
In 1997, NASA used the term to refer to a difficulty it faced: “[It’s] an interesting challenge for computer systems: data sets are generally quite large, taxing the capacities of main memory, local disk, and even remote disk. We call this the problem of big data.”
Indeed, although there seems to be no agreed-upon definition of “Big Data,” most definitions mention the problematic nature of the size of datasets. They refer to the logistics of accommodating the data, but, more significantly, also the trouble that old technology has with sorting and analyzing the new, gargantuan volumes of data.
Less formal definitions also talk about Big Data as an opportunity. Yes, the argument goes, we’re swimming in figures, stats, demographic numbers, and so on, but if we could harness them then we could build an analytical picture superior to anything we’ve ever seen before—and in just about any discipline. Or, to quote a blog post by data experts import.io, “more data is better, if you know what to do with it.”
How Does Big Data Apply to Marketing?
Big Data applies to marketing in countless ways. Here are just a few of the most important:
1. Advertising and content. The digital revolution may have made the promotion of products more involved—with new media, new platforms, new techniques—but it has made tracking and monitoring the performance of that promotion simpler. A good data scientist can help an organization experiment with its advertising and content, using digital information to determine what methods and messages are resonating with customers and which ones are falling flat. And then you’ve got the entire field of customer insights, which is so vast it really deserves its own article to do it even a hint of justice.
2. Pricing. Professional analysis of data can change the way organizations approach pricing. In 2014, McKinsey estimated that “30% of pricing decisions companies make every year fail to deliver the best price.
