Big Data is everywhere. In fact, SNS Research estimates that Big Data investments will account for nearly $40 billion in 2015 alone. These investments are further expected to grow at a compound annual growth rate of 14 percent over the next five years.
So why isn’t data already integrated into everything you do?
1. It’s too big
According to the 2013-2014 CUNA Environmental Scan, 10,000 payment card transactions are made every second around the world. Without tools to help you break down the data – to understand it, manipulate it, and put it to good use – data is too unwieldy to be useful. It’s like trying to use air as a business tool. Essential, yes. Manageable? Not really.
2. It’s awkward
“You can think of Big Data as sort of a class of 15 year olds,” said Eric Siegel, author of “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die,” in a story on Marketplace.org.
“Some (practitioners) are super mature prodigies, and they’re doing extraordinarily well,” he told the publication. “The rest of them are your standard 15 year olds who have so much potential, but they’re rough around the edges, so they may be doing things pretty effectively in order to get the grade, or in the case of online marketing in order to improve profit, potentially drastically. But it’s still kind of clumsy, kind of embarrassing, it’s kind of shameless.”
3. The infrastructure isn’t there
Ideally, analytics can improve your marketing efficiency and effectiveness, cross-selling efforts, operational decision-making, and more. Yet, according to Gartner, Inc., through 2015, 85 percent of Fortune 500 organizations will be unable to exploit big data for competitive advantage.
What this all boils down to is that in order for your analytics to truly reach their strategic potential, traditional work silos may have to be broken.
Leveraging Big Data Collectively
In a presentation to CUNA earlier this year, Samantha Paxson, chief marketing officer for CO-OP Financial Services, likened the process of managing big data to the evolution of dance. Integrating data strategically isn’t a matter of learning a few new steps: it’s about creating a whole new form.
In CO-OP’s case, marketing, product, and IT departments had traditionally been separate and distinct. But as data has became increasingly important in ascertaining and meeting client needs, these three departments learned to work as a collaborative unit:
“Working hand in hand with CO-OP’s product department, our marketing team has developed a much deeper understanding of the products we’re promoting – and why they might appeal to credit unions and consumers,” Paxson says. “In turn, CO-OP’s product team now thinks in marketing terms as well. So new features aren’t just cool or cost effective; they’re targeted toward specific credit union needs – or consumer expectations.”
So where does IT fit in? Everywhere that data lives, according to Paxson. She notes that for CO-OP’s more than three billion transactions processed annually for 50 million account holders, each is packed with information that the IT team must strategically manage and safeguard.
Connecting The Right Data Points
Filtering and understanding a reservoir of big data often requires the use of comprehensive analytic tools that go beyond the limits of transaction data to incorporate demographic information as well.
An ideal solution will allow your marketing, product, and IT teams to filter data for dates, times, locations, merchants, merchant categories, transaction types, and even individual card numbers for any given transaction. It should also be able to connect this information with both a merchant and member profile, including cardholder names and contact information.
“Your data is a reflection of your business, and it should answer specific business questions for you,” Paxson says. “Viewing business trends at the macro level is very important, yet so is the ability to zero in on the banking preferences and needs of individual credit union members.”
Not only can the right analytics tool inform your marketing initiatives, but it can also protect member data by allowing you to detect fraudulent activity with just a few simple mouse clicks – within minutes, not hours or days, Paxson adds.
Taking The Leap, One Step At A Time
At CO-OP, Paxson argues that deliberate collaboration between the marketing, product, and IT departments has made these groups stronger and more effective.
She also believes this kind of collaborative thinking is necessary for credit unions that want to make analytics matter. Data doesn’t integrate itself. One works hard to create a meaningful role for it.
“We live and die by our analytics,” she said. “We host three major websites, robust social media programs for both credit unions and consumers, and an active email hub. We are constantly looking for new opportunities while also maintaining privacy and security.”
As with all new undertakings, a transition to a data-driven workplace can be uncomfortable and awkward and will take effort and practice. It often requires a full commitment to reaching outside traditional boundaries and learning to work across accustomed roles in order to create something new and powerful.
If doing all this seems too big a task at first, Paxson suggests starting with more manageable actions:
“Get to know the tools that are available to help you get started,” she says. “And look for options that can be used not just to meet specific marketing or operational goals, but also as a basis for creating integrated marketing/IT/product-service teams.”
Integrating analytics into your big-picture strategy may indeed require learning a new form of dance, but it all begins with learning a few simple steps.
Learn more about CO-OP’s portfolio analytics tool, CO-OP Revelation, here.