Big data. The term may sound like the name of a spy agency file, but Bill Maynard has a more prosaic take on it.
“The term ‘big data’ has become a buzzword over the past 12 or 24 months,” says Maynard, managing director for Experian’s Global Consulting practice. “It has always been there, but it has become more accessible to the masses thanks to the increases in technology and raw computing power.”
The ability to quickly analyze massive amounts of data allows credit unions to “play in the ‘sandbox,’ ” he says. “That’s recently coined jargon for the ability of any financial institution to jump into a sandbox of data and analyze it as they like. In doing this, credit unions can compete with solutions that put them on an equal basis with much larger financial institutions.”
Brandon Bogler, product manager at The Members Group, says credit unions oft en fail to understand how much data they have. “Our specialty is aggregating data from multiple disparate systems to create a single member view. We draw from different data streams, such as credit, debit, marketing customer information file systems, and core data, and then present the entirety of its relationship with a member to a credit union.”
In addition to not knowing how much data they have, Michelle Thornton thinks many credit unions are not aware of what’s in it. “Finding out can be overwhelming,” says Thornton, manager, core products, at CO-OP Financial Services. That can cause credit unions to avoid learning how to exploit their data, she says.
On the flip side, many credit unions try to do too much at once. “The best approach is to take small, manageable steps that yield concrete, actionable results,” Thornton advises.
What to do with data?
Maynard says credit unions can apply their data in many successful ways.
“Thanks to leveraging ‘big’ data, an astute credit union competing against a giant bank in a particular region might pick up 1,000 credit card accounts off that bank,” he says. “While the bank doesn’t view it as a major setback, it’s a big shot in the arm for the credit union.”
CO-OP Financial Services, which markets a data warehousing and analytics tool called Revelation, can analyze a range of data based on card use.
“One of the beauties of the tool is that with the data we can access—date of birth, ZIP code, and transactional history—we can drill down incredibly far,” Thornton says. “We can determine how many 18- to 25-year-old members downloaded something from iTunes within the past three months. Or we can see which 32- to 48-year-old cardholders were in a sports bar on Sundays during football season. With this kind of fine focus, you can really segment marketing efforts and improve card use.”
But tools are one thing. Knowing how to use them and what you want to achieve with them are quite another. “Many credit unions want to understand our tools and services but lack a goal for how they want to apply insights from big data,” says Bogler. “Without that goal, they can’t really use the data effectively. The goal comes first.
“The chief information officer or chief data officer must be involved in data architecture and structure with new credit union initiatives,” he continues. “Their task, in view of the credit union’s goal, is to create appropriate aggregation, storage, and ease of access to big data.”
Bogler says The Members Group presents its conclusions about a client’s big data in the form of a set of recommendations and interpretations. “We may note, for example, that a credit union has 500 members who have auto loans, home loans, and credit card accounts, but not debit cards. We can recommend approaching them based on data we have that shows their propensity to accept offers and which offers to make.”
Big data and marketing
Obviously, big data can have a profound effect on marketing. “Many credit unions have in-house marketing departments that possess the resources to execute a targeted marketing campaign,” says Bogler. “Others will ask us for recommendations and best practices. In that case we act as consultants and direct them to trusted partners who routinely execute on these types of campaigns.”
One factor that has been emerging during the past 12 to 18 months, he says, is the need to approach a younger demographic with digital media marketing campaigns. Digital’s cost efficiency and speed to market are impressive and much less expensive than traditional directmail campaigns.
“We can help from a marketing perspective, such as conducting quarterly campaigns that target certain segments,” says Thornton. “For example, we’ll focus on members who use their cards for five or fewer transactions monthly and incent them with a reward to do 10 or more per month. We go in, identify the cardholders, create and send out branded marketing materials, track the responses, fulfill any rewards, and provide results.”
She says the results from such efforts can be long-lasting: Some 85% to 90% of cardholders do not revert to their old behavior. Their increased card use is sustainable.
“Another benefit is mining data for cross selling,” Thornton adds. “Some of your most active debit card users may not have one of your credit cards. Identifying them lets you market to them.”
Maynard says that while his company’s predictive toolsets and platforms are powerful—“We can tell XYZ Credit Union that member Bill will be in the market for a credit card within the next 30 to 120 days”—credit unions still have to thoroughly think through their offers, and that offer-alignment is crucial.
“We’re currently working with a credit union that’s not pleased with its credit card portfolio marketing activities and lack of success,” he says. “The offers it’s making aren’t compelling to its member base. The current product being offered is a standard nonperk card aimed at revolvers—people who run high balances and oft en make just minimum monthly payments.
“The data show that members taking on more cards from other providers were exhibiting more of a transactional behavior, not revolving,” Maynard continues. “We’ve suggested changing that approach to identify and target transactors—people who use their cards actively but pay them offmonthly—with a platinum product that has a higher rewards focus.”
Big data best practices
The best way to embrace big data tools is to use analytics proactively, Maynard says. When examining members’ behavior, too many credit unions consider only the internal services members use, not those from other providers. Big data should be all-encompassing.
“Suppose you learn that a member is delinquent with outside accounts,” he says. “Isn’t that something that’s helpful for a credit union to know so risk and marketing strategies can be adjusted accordingly?”
Also, credit unions can use big data tools to make sure their products and services are competitive with those of other financial institutions, Maynard says. “We call this ‘benchmarking against the footprint.’ With many large financial institutions continuing to expand their footprint and reach, competition continues to increase.
“But credit unions don’t have to be cutthroat competitive against larger financial institutions,” he continues. “If they make the right offer at the right time, a member’s natural affinity may be enough to tip the decision in favor of the credit union’s offering.”
The idea, Maynard says, is to stay in the running with offerings that members will seriously consider.
It’s also important to monitor social media for comments about the credit union, Bogler says. You can use the data to assess how the public perceives you, and what changes you might make in light of what you learn.
Thornton says CardNav, a new mobile app from CO-OP Financial Services, allows cardholders to control how their cards are used. “They can specify, for example, that the card can only be used within a certain distance of the cardholder’s mobile device, limit its use to certain merchants or geographical areas—or even turn it off and on.”