“Does your credit union have a data solution and do you have confidence in it?” THAT is the question. The world of data is ever-expanding, and every day we’re amassing 2.5 quintillion bytes of data. (For the record, quintillion is a number ending with 18 zeros.)

When working with our credit union partners, I open the discussion on analytics by asking this simple question. All-too-many times I get the quick response of “Oh, well we have a data warehouse, so we have all we need.” This is always an interesting response because it really exemplifies the unknown opportunity in the movement towards actionable data.

The best comparison I tend to draw for our partners is by asking if they’ve ever stepped into the tumultuous world of furniture building, a la IKEA. Customers travel miles through a furniture warehouse to gather the pieces of a desired Swedish bookshelf. Once back home, they are greeted with an instruction book complete with pictures that make as much sense as a dog learning Klingon. This is all to say, having pieces of the data won’t inherently lead you to the desired end result, and, instead, one must look to building a story using enriched data elements.

So why should you not rely on a data warehouse as your only data solution?

  1. Time

According to multiple studies, data warehouses can easily take up to 3 years to be built and fully implemented. Unfortunately, as we all have surely learned, technology moves fast, and after 3 years of development, it’s likely that your data needs have grown. This is why according to a TDWI study, 50 percent of business owners that build a data warehouse solution identify themselves as at least “somewhat behind” if not “completely behind” their own business technology needs.

  1. My data’s “where” house?

Data siloes are seen in all businesses and especially financial institutions. With a constant need to stay up to date, we see credit unions put one data set in one platform and then a different data set into a different platform. Inevitably, this leads to issues where different departments are pulling different data sets for the same information.

  1. Staffing

Most credit unions we see simply don’t have the resources available to them to build, maintain, and analyze data from data warehouses. These implementations require highly-skilled workers that come at a premium cost.

  1. Money

All 3 of these previously mentioned concerns add up to a huge cost to the credit union. Whether it’s bringing on a data scientist or implementing new reporting software, data warehouses are a costly investment. It can cost millions in upfront set-up costs and this doesn’t include the added cost of the aforementioned issues. Additionally, a recent study  says that 50 percent of data warehouses don’t reach full adoption or actually fail.

At Franklin Madison, we’re taking a targeted approach in continuing our work to not only increase our actionable data, but also make sure that we set up our credit union partners for greater success by providing them the same insights into their membership. How do we achieve this? Collaborative analytics.

Franklin Madison partners with Acxiom, one of the world’s most comprehensive data providers, to securely transmit credit union files and append several of their marketing-driven data elements to these files. The enhanced data elements allow us to strategize and build better models for marketing. With these enhancements, we are able to see significant lifts in response rates, as we are able to more appropriately craft our messaging and work with the credit union to select the members for this messaging. Where the real collaboration begins is when we work to package together all of these data insights into an aggregate report for our credit union partners to utilize for their own internal research. This complimentary reporting, called LUX 360°, provides a new level of insight into our actively marketing partners’ membership by providing them access to demographic, behavioral, and financial data provided by Acxiom. These additional attributes can give our partners a significant advantage in the ever-competitive credit union market.

This collaborative approach to analytics allows us to build a mutual relationship with our credit union partners where transmitting data between each other is not just another task to check off of a transaction list. It has become a structural component to building out our joint effort in engagement and success between a credit union and their smarter marketing partner at Franklin Madison. The data is already at your credit union’s fingertips, and, inspired by the infamous words of Vanilla Ice, we all need to:

  • Stop silo’ing our data into warehouses
  • Collaborate with our partners
  • And listen to what our data can truly tell us