Credit unions store much more member data today than in years past. Everything from transactions to inquiries, text messages to online reviews serve as the basis for a virtual treasure trove of consumer insights and applications. The trouble is this data is often sourced from and stored in disparate sources, making it incrementally more difficult to perform meaningful analytics.
When and how to tap into this data are questions facing leaders in the movement. Among those contemplating the answers, some of the more inquisitive are beginning also to wonder if data has the potential to be monetized.
Can credit unions sort, analyze and manipulate their data and then put it to revenue-generating use? Yes, but first, they must master the art of merging data to create a single (and marketable) view of members. This would illustrate for credit union staff, as well as potential partners, how a member or segment of members behaves across products.
Getting to that single view of the member will help the credit union’s leadership make better decisions in each of the following areas:
Risk: If a member has a loan and a credit card account, for instance, a single view will allow lending teams a clearer picture of that member’s payment history. With the increased information, these professionals can manage accounts more aggressively and offer competitive pricing and promotions that fit the complete risk profile of the member.
Marketing: Leveraging history and response behavior across campaigns and departments will allow marketers to create highly targeted offers to members, greatly increasing the chances of success.
Member service: If we know a certain member works best with a certain staff member, we can try and route calls to that employee. If the member comes online, we can display web content most relevant to him or her based on previous online movements.
Better risk, marketing and member service decisions will lead to a greater overall consumer experience, and ultimately, a greater influx of revenue as members take advantage of personalized products, offers and service.
A slightly more advanced way credit unions can monetize data is to use the information to forge partnerships with local merchants. Here are a just a few ways this can work:
Merchant based incentives: Credit unions can partner with area retailers relevant to members based on transaction history. This will allow both the credit union and the merchant to market highly targeted offers. The credit union expands its value proposition, and the merchant experiences an increase in demand.
Friend-get-friend offers: By monitoring the social postings of members and identifying the opinion leaders among them, credit unions can advise merchant members on where their marketing dollars are likely to have the greatest impact. Credit unions enhance the value of their relationship to the merchant, while the merchant increases the return on its marketing investment, and of course, sales.
Strengthen local businesses: As neighborhood-oriented financial institutions, credit unions often understand better than any other entity which businesses in which areas of a particular geography are struggling. Providing a cash-back rewards option with these merchants based on the propriety data of the credit union can go a long way toward helping these small businesses thrive in what is becoming an increasingly competitive environment. This will help the credit union further engage its members with better and more local alternatives.
Big Data can open new revenue streams by boosting the value of those relationships most important to your credit union – but only when properly synced and analyzed. Developing the capabilities to complete this type of work now will not only generate more income for the credit union; it will position your teams for success as consumers and merchants alike demand a more personalized experience.