Innovation. It just might be today’s most popular buzz word. Some other buzz words we hear way too often these days? Automation. Data. Efficiency. Do you know what industry puts these words into action to achieve great things? No—sigh—it’s not the credit union industry that I LOVE. It’s the recycling industry, which—sigh—I love just as much as credit unions.

Recycling, single-stream recycling to be specific, is one of the coolest, most innovative industries out there. And just like credit unions, single-stream recyclers want to do good things.

The other day, as I was happily scrolling on LinkedIn, a video caught my eye. (Ahh, the irresistible appeal of conveyor belts with recyclables speeding by!) After watching the video, I read this corresponding blurb above it:

“We are testing small OCC recovery from the unders of a commercial OCC screen this morning with a client at our new test facility in Norwalk, CT. Ask us when we can set up a test with your material. Not sure what you want to recover? Our continuous loop system gives you the option to blend material back together or separate what you have recovered for further testing. We will try anything you can think of!”

I know most of the people reading this post won’t have any idea what the quote is referring to, but in addition to being mesmerizing to watch, the single-stream recycling video and accompanying blurb essentially summed up how I feel about data.

When I talk to CUs of all shapes, sizes, and demographics and I ask how they are using the data that’s available to them, they all say, “Well, we use it to target by age, balance, or product type.” Nothing surprising or unique or complicated. Do they see results? Of course. Maybe not HUGE or earth-shattering results, but with minimal effort put forth, something is better than nothing. And, in most CU scenarios, this is 100% OK. These are our safe targets.

But if you are a digger (aka – a pot stirrer, cage rattler, etc.) like me, the kind of person who routinely asks “What if” or “Why?” or “Can we?” or “What about those other members?” … then you need to do another pass through of your initial data and dig deeper into the “unders.” The “unders” can be defined as the members that might not make the initial screening. Maybe they are borderline on credit score, ratios, or age. But whatever the case may be, they slipped through your initial screening even though they might have potential value. In many cases, the value of the “unders” can be greater than the members that make the first cut. Whether “value” is viewed as member loyalty (because we are talking credit unions) or interest income (because we are talking balance scorecards), both will add to your credit union’s bottom line.

Like the video shows or the caption says (if you’re not the least bit interested the really cool video of innovation in action), you can reblend or separate the data further to find new targets you hadn’t considered. Then, you can tweak the offer to connect with these newly identified targets. Imagine how beautifully relevant your offer could be! Talk about WOWing your member and making them feel special!

Let’s look at a hypothetical example:

Your Credit Union is getting ready to roll out a new credit card. Maybe it features a cash back option or some other reward. You are extending this offer to members who have been with your credit union for at least six months, have B+ credit or higher, have X dollars in a share account, and have a checking account with direct deposit with NO negative behaviors.

You have 5,000 members over the age of 21 that you can market to. You have a 63% checking penetration, which amounts to 3,150 members. 22% of these members have a B+ or better credit score, so, you’ve narrowed the potential recipients to 693 members. If 10% have had some negative behavior, you’re down to 623. Of those 623, only 600 have been a member for longer than six months. (Hopefully your credit union has much better onboarding than my example—but that’s another conversation for another day.) Anyway, you’ve identified 600 members. Out of 5,000.

What happened to the other 2,550 members that fit the first criteria? These are your “unders.” Maybe you have an additional 600 members on the cusp of a B+ credit. If you give these members the same perk-filled credit card, perhaps they will appreciate the offer—and you for making it. Then, due to the goodwill you’ve created, your credit union’s card gets the coveted default payment spot at the top of your member’s digital wallet. With results like that, finding those “unders” is certainly worth a second look, isn’t it?

Now it’s time to ask yourself a few questions. Where are your “unders?” What do you want to recover in your data stream? Where’s your profit? Where’s your member value?

The answers are right there in your data. Sometimes you just have to look for them—one more time.