Big Data, Big Decisions
Can you go more than a day or two in your business life without hearing somebody reference “big data”? It sounds ominous, like some hulking monster lurking around a dark corner, just waiting to jump out from the shadows to get you—and to some degree it just may be.
Big data is having a big impact and it goes far beyond the “you might also like” tips we get when we’re buying a song on iTunes or shopping online. Algorithms are at work sifting and sorting reams of data matching our tastes with literally millions of other related possibilities.
In a now somewhat famous example of big data, Target figured out that a teen girl was pregnant before her parents knew. When an angry father asked a Target manager why the retailer was sending his teenager coupons and incentives for infant-related merchandise, the store manager apologized—but later received a call from the upset dad who shared that his daughter was, in fact, pregnant.
The big consulting firm McKinsey forecasts $3 trillion in economic value from businesses making better use of data, a lot of that from discovering how to do the same job or task better, such as laying out a supermarket’s traffic patterns, or the optimal times to transport freight.
While the amount of data marketers have access to is unprecedented, it’s how that data gets “crunched,” or interpreted, that’s key to turning information into insight. And of course there are the decisions made based on that insight. A seminal article in Harvard Business Review says that a company should focus its big data marketing on five primary categories: market conditions, competitive activities, marketing actions, consumer response and business outcomes.
Here’s an example of putting big data to work in an insightful way: A real estate investment and management company owned properties in a college town and was looking for a way to make them more competitive. Newer properties with amenities like swimming pools and fitness centers were taking its market share. Enter big data. The property company found that while amenities like fitness centers and swimming pools ranked high on tenant wish lists, next on the list for students was a quiet place to study. Based on that insight the real estate company began marketing to more serious academic students and even offered discounts to those with high grade point averages. Occupancy rates rose to over 95 percent.
Another example comes from the world of entertainment and online streaming giant Netflix. Data analysis of viewer habits showed its viewers stayed to the end of movies directed by David Fincher or starring Kevin Spacey. It also gleaned that the British drama House of Cards had unusual staying power, remaining popular some 20 years after its original release. While those factors were not the only considerations in the development of the U.S. version of House of Cards, they were important validators of Netflix’s risk.
What’s happening is that businesses are able to synthesize and centralize data across multiple channels such as mobile applications and e-commerce sites, social media accounts and points of sale. Transactions and preferences based on actual purchase behavior—as well as interactions—can generate customer profiles more advanced than previous segmentation analysis, which in turn allows marketers to develop more strategically targeted messaging, offers and campaigns—not to mention products and services. It can even be used to better inform sales reps about customer personalities and preferences.
Automation also plays a huge role in how big data gets used. By connecting our digital behaviors with customer relationship marketing software, marketers can “learn” the products and subjects we’re most interested in and then can automate software to send information—excuse me, content—that relates to our interests. What we click on next and how much time we spend with whatever we’re shown—as well as whether it leads to a purchase or request—gets fed into our profile, and the software gets smarter predicting what will interest us.
Given all the possibilities, it’s no surprise that within a few years the data budgets for chief marketing officers are expected to surpass the technology budgets for IT departments. Will all the information, insight and automation eventually suck the creativity out of marketing? I doubt it. I mean, can you think of some algorithm coming up with something like the ALS ice bucket challenge, or any of the other marketing programs that have gone viral? I think that the smartest marketers realize that while big data can direct, it shouldn’t dictate.
Glenn Karwoski (email@example.com) is founder and managing director of Karwoski & Courage, a marketing communications agency. He also teaches in the graduate school at the Opus College of Business at the University of St. Thomas.