For most credit unions, the concept of using data analytics to better meet members’ needs is not an unwelcome innovation. With a reputation for hands-on service, it should be no surprise that the majority of credit unions have strategically committed to using digital services and data analytics to:
- Serve members
- Acquire new members
- Increase sales of products and services
- Make credit decisions
Many are also prioritizing and committing new resources to credit union data analytics, decisioning and improving operations. To compete on a level playing field, they’ll also need to concentrate on marketing strategies which support growth, income creation, and lowering expenses.
Real Results from Data Investment
Figuring out the types and quantity of data which should be collected and analyzed is a complex process. Credit unions have historically been focused on servicing their members, so data has traditionally been limited to account-level information. But if the goal is to gain market share, increase income/capital, and enhance their brands, a different approach is required.
Here are three ways the fastest growing institutions, like Illinois-based Baxter Credit Union, are using data analytics to improve their marketing, sales, and service results.
- Every offer is a targeted one. Whether someone is looking for a home, car loan, or reviewing retirement options, that data is captured and used to send them the right response – on the right device to offer them solutions, including pre-approvals. This leads to improved response rates.
- Performance data is used for member insight. Analyzing their own and third-party data, credit unions are learning how to increase their performance rates by looking at issues on everything from risk to delinquencies. From the member side, they’re looking to data to show them where there are service interruptions or service performance needs. Does their social media analysis provide insight into what members don’t like about their digital experience? How do they rate their online interactions?
- A member’s positive experience still ranks #1. Whether it’s over customer wait times or increased security, one in five customers who switch financial institutions do so because of a bad service experience. Data analytics-driven credit unions are better equipped for retaining members through positive online and in-person interactions. For example, they survey their members for feedback and use that data to improve the overall member experience.
What all high-performance credit unions deeply understand is that data analytics is a dual-purpose endeavor used for servicing members needs and improving their organization’s results. Put another way: they know that credit union data analytics is the path to a hyper-personal banking relationship and the way to improve their marketing efforts and sales operations.
So, Where to From Here?
Many credit unions are making increased investments in tools, data models, and the skills needed to create a better use of data. These investments bode well for improved growth and customer service. Those who aren’t using data analytics may point to hurdles like a shortage of in-house expertise, lack of financial resources, or the inability to obtain valuable analytical insights, but these arguments will not prepare them for future (or, for that matter, present) competitiveness.
All credit unions must embrace today’s data-driven concepts and strategies if they hope to effectively compete in an ever-evolving financial world. Their growth and heightened member experience are dependent on it.