Using “Big Data”, that is accessing and cross-referencing the many data troves on credit union members in order to cross sell, has been the subject of many white papers and conferences. Analyzing purchase transaction data, cash withdrawals, ATM transactions, and recent balance transfers can paint a very accurate picture of a member, and help formulate marketing to retain that member and ideally provide additional products. And, there are many success stories of slicing and targeting cross-sections of member demographics to derive offers resulting in take rates that exceed industry averages for cross-sell take rates.
But accessing and using big data requires a lot of resources including the analytical tools and reporting software to mine the data, hiring professional staff to perform the analysis, and utilizing consultants for training. These resources add up to a burden too heavy for many medium- to small-sized financial institutions. However, there are simpler and faster paths that do not require the investment in big data. A credit union can use “little data” for the same purpose. For example, one credit union had great success by doing two simple queries – members who have a CU-branded credit card, and members who have over $500 ACH pulls or bill pay payments to one of the two very large credit card issuers. Those members who already had a CU credit card were sent a direct offer to make $500 a month in purchases over the next three months and get a large rewards bonus. This was to get the CU’s credit card to move to top-of-wallet. Those who didn’t have the CU’s credit card (and met pre-screen criteria) were also sent a direct mail offer for the CU credit card with an initial bonus offer, thereby doing cross selling. The results exceeded all expectations, and the costs incurred included some direct mail pieces and a few hours of the IT analyst’s time.
Another credit union had similar success targeting members who had ACH or bill pay payments made to local utilities that accept credit cards, cross referenced with existing credit card cardholders. Once the data was compiled, the CU sent a direct mail piece reminding them that rewards could be earned for using their credit for payments they were making already.
There are many such “low hanging fruit” to go after with simple tricks and some simple data queries, limited only by the cleverness of the credit union staff to come up with ways to build up the relationship with their members.