The big data hype is officially dead.
In 2015, the analyst firm Gartner dropped big data from its Hype Cycle for Emerging Technologies report. The newer fields of Internet of Things and autonomous vehicles (also known as self-driving cars) replaced big data on the list.
But as Nick Heudecker, analyst at Gartner, is quick to point out, the exclusion of big data from the list isn’t a sign that this field is obsolete—it just means big data is now the new normal.
Here’s a look at the rise of big data hype, its untimely death and what it all means for for marketers, researchers and other business professionals who use customer intelligence.
The rise of big data
Big data refers to the massive amount of information amassed digitally—every time we watch something on cable TV, buy airline or concert tickets, purchase something in a department store, do just about anything online and so on. Big data also refers loosely to the analytical tools employed to make sense of all this information.
Big data is ubiquitous, it’s growing and it’s getting tougher and tougher for companies to understand.
As early as 1990, Peter J. Denning, then the director of the Research Institute for Advanced Computer Science at NASA’s Ames Research Center, was worrying about how his fellow scientists could ever extract meaning from the ever-growing sea of data they collect: “The imperative to save all the bits,” he wrote, “forces us into an impossible situation: the rate and volume of information flow overwhelm our networks, storage devices and retrieval systems, as well as the human capacity for comprehension.”
By 2010, the term “big data” had entered the common lexicon. “Data, data everywhere,” a 2010 article in the Economist, cited Walmart’s one million transactions every hour, Facebook’s 40 billion photos (by 2013 that number had jumped to 250 billion, and was increasing by 350 million each day), and one-week analyses of the human genome’s three billion base pairs as illustrative of the world’s “unimaginably vast amount of digital information.”
“The effect is being felt everywhere, from business to science, from government to the arts,” the Economist continued. “Scientists and computer engineers have coined a new term for the phenomenon: ‘big data’.”
Big data is not just about digitizing existing information. It’s about rendering more of our lives into data in real-time—where we are, what we like, with whom we interact, what and when we buy and more. Social media platforms such as Twitter, LinkedIn, Facebook, Snapchat and Instagram are examples of the real-time datafication of customers’ lives.
The big drawback of big data
More and more companies are harnessing the power of big data to help guide strategic business decisions and gain insights into customer behavior. Many of these companies, however, are realizing that big data alone is an inadequate source of customer intelligence.
One major issue is lack of strategy. Companies have access to a lot of customer information, but they don’t really know how to leverage it to make good strategic decisions. Without this foundation, adding big data into the mix often adds little value.
More importantly, big data lacks actionable information with which marketers, insight professionals, customer experience leaders and innovators can make effective decisions that benefit their customers and their bottom line. Big data can reveal much about what’s going on, when it happens and where it happens. But businesses haven’t really arrived at the day when big data can reliably tell us why customers behave in a certain way.
Getting to the why
As computing advances and analytical tools progress, we may someday get to a point where big data can help reveal the why. But for the foreseeable future, big data is only one tool in the marketer’s toolbox. Customer intelligence that involves more direct human-to-human interactions with consumers remains vital. Big data will only take us so far, and at some point a human perspective needs to join the effort.
For insight departments to derive value from big data, they must get better at leveraging social science, data analytics and consumer insight. Understanding the nuances of customer behavior—the motivations, or the “why” behind behaviors—gives us true insight. And that cannot come from a centralized and isolated big data department.
Computer technology, the Internet, cable entertainment and other technological advances have led to empowered customers who have more access to information, more choices, more demands on their time and, in many cases, less allegiance to individual brands and companies. At the same time,customers spend more of their lives and their shopping hours online.
When it comes to buying, customers have unprecedented access to information about companies and the products they sell. Big data surely has a role to play in gaining insight into the behavior of these empowered customers.
But as we’ve discussed, big data doesn’t have all the answers. Companies need to respond quickly to identify changes in customer behavior and take action to address their concerns. Big data can offer some answers, but continual human-to-human connections are required to fully understand the rapidly evolving marketplace.
Using customer engagement to humanize big data
The death of the big data hype just means that big data is now mainstream. With it comes tremendous insight into customers’ daily lives, their needs and desires, their personalities, and their rapidly evolving tastes and loyalties.
The digital world we live in has sped up everything, and it’s hard to keep up. We’re only human, after all. While big data and smart analytics can help us understand our customers, it can’t yet provide a complete picture. And that’s where human intelligence comes in—human-to-human connections that provide a company with insight it can get nowhere else.