4 Ways To Turn Data Analytics Into A Credit Union Differentiator

The smart use of data analytics can turn a credit union’s communications strategy from potentially creepy into authentically clever.

 
 

Analytics has been a major topic for some time among credit union strategists and is only growing in importance. Meanwhile, using analytics ethically has come to the fore globally, with the May 25 go-live date for the General Data Protection Regulation by the European Union.

The GDPR might not directly impact credit unions that don’t have members in Europe, but it’s a new bar for such things as reporting data breaches and obtaining consent for data use.

The idea is that users of consumer data — like credit unions — need to do so ethically. Now, “ethically” to one organization might mean something different from what it does to another. Determining what is ethical is a tough question every credit union needs to answer in its own way, and the answer might not remain the same over time as channels and products evolve.

 

 

 

Additionally, new standards will arise to help credit unions define the line between “convenient” and “creepy” and maybe even cross into “clever.”

For example, if I search for boots on Zappos, I know I’ll see Zappos ads on every internet site I visit for the next few weeks — all displaying the exact footwear I was looking at.

That seemed creepy a few years ago, but it’s now commonplace for sites to track what people are looking at and customize the ads. Consumer perceptions have changed, and with it, the line between creepy and convenient has moved.

Searching for products online is a pretty straightforward example. But what about something more private, like Google offering ads within Gmail based on private messages? For example, if someone sends an email to a friend that says, “I want to buy some new boots, but I have to make a payment on my student loan,” and suddenly starts getting ads for loan consolidation services.

Email providers “reading” emails and targeting ads. That’s unethical, right? Downright creepy!

Analytics at work is only as creepy as the sender is — or is perceived to be. If your members see you as a valued financial partner, then knowing a lot about them and anticipating their needs will come across as reassuring rather than as intrusive.

Alix Patterson, Partner, Callahan & Associates

But what if a similar message comes from the email sender’s credit union? And the central message is about how much the credit union can save its member by refinancing their student loans at a lower rate? And the credit union throws in financial counseling for good measure?

That message might not feel so intrusive. With some imaginative marketing, a member might welcome it. Think along the lines of “big brother isn’t watching out for you, but we are.”

Here’s another use case: A member searches for cars online and then receives an email from their credit union with insight into their credit score and advice on how to negotiate a better purchase price. Maybe the message even offers a referral to a dealer. Or better yet, an offer to provide a referral. Opt in. Opt out. That feels even less salesy.

Analytics at work is only as creepy as the sender is — or is perceived to be. If your members see you as a valued financial partner, then knowing a lot about them and anticipating their needs will come across as reassuring rather than as intrusive.

But that raises more tough questions. First, is your data analytics capability up-to-date, and advancing with the times and the competition? Second, is how you use this insight member-focused enough?

In the conversations Callahan has with credit union leaders, including during organized settings like the firm’s executive roundtables, topics about regulatory rules and consumer expectations around consumer-friendly data pop up. And they will more frequently going forward.

“Consumer-friendly” is synonymous with “member-focused” for the purposes of this discussion and for the discussions your management should be having around data analytics strategy.

It’s Time For Tough Questions

Asking tough questions helps the credit union movement flourish. Make Callahan’s Tough Questions commentary on CreditUnions.com a regular stop for insight on thinking differently about the movement and framing strategies for success.

Read More Commentary

Here are a few ways the movement’s leaders have discussed using member-focused data:

  • When a member regularly uses an ATM that’s not part of the credit union network, let them know when there is an in-network option nearby. The credit union might lose some fee income, but it’s the right thing to do. The member will see that, too.
  • If a member spends a lot of their income on expenses like wireless and cable bills, let them know they could save through a negotiation service like BillShark. The credit union might lose a bit of interchange income, but again, it’s saving the member money. Take it a step further and consider partnering with a firm like this to get better deals for members.
  • Track how each member uses the credit union’s digital offerings and display those features on or immediately after the log-in screen. For members who rarely do anything but check balances, offer to set them up with balance alerts so they don’t have to log in at all.
  • Watch for members whose credit scores suddenly drop, who suddenly lose their income, or who get behind on loans. Reach out to help. See what’s going on. You have the data — be proactive.

Yes, the last two items are different from the first two, but all four speak to improving the member experience by knowing the member.

Conversely, don’t alienate members by making offers that show you don’t know them at all. For example, don’t send auto loan offers to members who just took out an auto loan from you. And don’t send home equity offerings to non-homeowners. Don’t laugh. It happens.

The world’s most successful e-commerce shop, Amazon, has intimate knowledge of its customer baked into its mission statement: “Our vision is to be Earth's most customer-centric company.”

It has accomplished that mission by pushing the envelope, developing and deploying ever-more sophisticated ways of determining what people want, and finding the most efficient way of giving it to them. Amazon, and other tech giants, has armies of bright, motivated, talented people working on data strategies. Credit unions can’t compete on that scale, but they don’t have to.

Member-owned financial cooperatives have the power of collaboration and the cachet of purpose, of serving the collective good. That appeals to bright minds out there who want to add altruism to their algorithms.

And by any measure, that’s not creepy.

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June 11, 2018


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