If you’re in management, marketing or IT, you’ve undoubtedly heard the term “big data,” but do you know what it means – and what it means to your credit union? If you’re a little embarrassed to admit that you’re not quite sure, rest easy: You’re not alone.
Though the business world is buzzing about big data, the term means different things depending on whom you ask. In general, “big data” is used fairly loosely to describe all the data an organization generates. This can include both internal data (such as point of sale data, ATM records and website browsing histories) and external data (such as social media data, surveillance data and public databases).
“I see people defining big data in three buckets,” says Ron Shevlin, a Senior Analyst at Aite Group, a Boston-based research and advisory firm serving the financial services industry. “One is defining it as extraordinarily large datasets that exceed the computing capacity of most PCs or traditional databases. The second alludes to the integration of qualitative or unstructured data with more traditional structured data – for example, integrating social media data from Twitter or Facebook with traditional spending or demographic data. The third, and most troublesome to me, is people using it to allude to any use of analysis or analytics.”
Shevlin, who notes that financial services companies have been analyzing huge datasets for decades to detect fraud or pre-approve credit cards, believes too many vendors pushing “big data” tools are simply trying to cash in on a poorly defined management fad.
BIG DATA’S PROMISE AND PITFALLS
But just because big data is still rather nebulous doesn’t mean you can ignore it. Properly used, big data has great promise for businesses. Research by McKinsey & Co., New York, N.Y., found that effective use of big data helps companies make better, faster management decisions; segment customers more narrowly to develop precisely tailored marketing campaigns, products and services; and compete more effectively in the marketplace.
“Banking is such a commodity that you have to build differentiation,” says Bryan Clagett, Chief Marketing Officer at Geezeo, Tolland, Conn., an online financial management solutions provider for banks and credit unions. Big data can help. “Data about the convergence between members’ online social media activity and their offline activity can help credit unions get a better understanding of how we’re relevant to our audiences so we can build differentiation with our brands.”
But for credit unions, the challenge may lie not so much in gathering more and more data, but simply in making better use of the data they already have. Existing analytics programs, PFMs (personal financial management) and MCIFs (marketing customer information file) are treasure troves of data that credit unions too often fail to mine effectively. “Transactional data, whether it’s gathered at the time of a loan offer or closing, through ATM networks or through credit card analysis, is remarkably useful and readily available today; it’s just not translated into easily digestible information for credit unions to use,” says Clagett.
Shevlin agrees. “Few credit unions analyze or make good use of their PFM data,” he notes. “Understanding spending patterns can help you identify cross-selling opportunities, marketing opportunities or financial education opportunities. For example, if a member is continually overdrawn, clearly they need financial management education.”
Even those credit unions that do access and analyze their existing member data frequently fall short when it comes to acting on what they learn to develop new products and services, market more effectively or provide better customer service. “Credit unions have a lot of information that could be leveraged, but isn’t,” says Clagett. “I use the same ATM every week, and it always asks if I want English or Spanish.” What if “big data” helped you make even small gestures toward recognizing your members?
TO GET BIG RESULTS, START SMALL
In fact, starting small may be a good strategy. “People get hung up on the big data label,” says Clagett, “but information from ‘small data’ can be just as valuable. For instance, if a member has a savings account, what are they saving for? Why do they pick one credit card over another?” If you access this information, Clagett says, you’ll be better able to provide relevant offers.
Instead of thinking in terms of big versus small, Clagett believes, credit unions must think in terms of better data. “What is available to us, and how can we leverage it better?”
Start at the top, with management clearly defining the business problem, challenge or opportunity. “Then figure out what information you need to fix this problem or capitalize on this opportunity,” says Shevlin. “If using large sets of data will help, go for it. But don’t do big data just for the sake of big data.”
Your credit union’s top-level management, marketing and IT team must sit down to determine what data exists both internally and externally and what insights they hope to obtain from it. “Identify that from a leadership perspective, and create a scope document that allows the tech people to work with you to present the data in a meaningful way,” says Clagett.
Be sure to engage your existing vendors. “Your MCIF provider, online banking provider, PFM provider and core provider can all work with you to help you better use the tools you have,” says Clagett. In fact, he adds, these vendors are frequently frustrated that their products aren’t fully leveraged, and are eager to help you get more from them.
Information you may want to gather includes channel preferences, what types of interactions take place in the branches, which members use a branch and which prefer to bank online, which members have children and how old the children are. “Even understanding which customers use iPhone versus Android platforms affects where you put your resources,” says Clagett.
MAKE IT WORK
You can gather and analyze data until you’re blue in the face, but your newfound knowledge means nothing without the most important step: using it. “People are spending all their time analyzing data,” says Shevlin. “They say, ‘We’ve got great opportunities. 33 percent of our customers want XYZ.’” But too many fail to take the next step: determining how best to capitalize on those opportunities.
What marketing tactics work best to spread the word to members and potential members? Shevlin says testing messaging is crucial to success. “How do you actually get the message in front of them that you have the solution they want? How often should you send that message? Will sending one e-mail work? Not enough firms are testing various approaches to messaging, creating media mix models to allocate spending across various channels, or building contact cadence models to figure out the optimal messaging frequency. This is as much art as science.”
The results of using data properly can be impressive. One credit union that used CO-OP Financial Services’ CO-OP Total Revelation to identify inactive cardholders and enter them into a drawing got a 24 percent response rate and generated $2 million in purchase volume in 60 days. They’ve gone on to use CO-OP Total Revelation to identify and contact inactive members 30 days before their accounts are about to be closed and offer them an incentive for making transactions, as well as to identify members with recurrent NSF (non-sufficient funds) transactions to offer them opt-in to overdraft accounts.
Should your credit union be worried about integrating big data from social media into your strategic and marketing plans? While the answer may vary, for the average credit union, social media is so far more valuable as a member engagement and listening tool than as a data stream.
“I’d advise most credit unions to not even be thinking about social media data,” says Shevlin. “Yes, they should monitor the social media environment for mentions of their credit union, and use social media to engage members and prospects.” But in a recent survey, when Aite Group asked banks and credit unions how many times a month their credit union was mentioned in social media channels, “the vast majority said 10 times a month or less,” says Shevlin. “That’s not big data.”
Last, but not least, as you mine your data, keep trust in mind. “At the end of the day credit unions are about commerce, which all depends on building trust,” says Clagett. “But consumers may feel that you’re using their data in a way that makes them uncomfortable.”
To build trust, ensure you have a clear and present opt-out whenever possible; that data collection is not invasive; and that members understand the value the data collection brings to them – whether that’s savings, better products and services, or faster responses to their needs. “It’s easy to gather data and either do nothing with it or do something wrong with it,” says Clagett. “Breaking that member’s trust is very damaging.”
What does the future hold for big data? Clagett believes that a deluge of information about shopping and merchant transactions will be the next wave. “Through card processors and ATM processors, we’ll get a better idea of how people manage, spend and save their money,” says Clagett. “Nontraditional financial institutions are already collecting and leveraging a lot of this data. By getting a feel for the financial experience a consumer is seeking, they’re really empowering the consumer. Credit unions need to do that as well.”
Karen Axelton is Chief Content Officer of GrowBiz Media, a media and custom content company focusing on small business and entrepreneurship. Visit her website, SmallBizDaily.com, to sign up for free TrendCast business reports.