August 19th, 2022
This month, Maddaux and Anne Legg, Data Analytics Wizard at THRIVE, help guide credit unions who know they need to implement a data analytics program, but just don’t know where to begin. Creating a strategy can be overwhelming, especially for non-technical folks.
The Cuery Data Analytics team is here to help if you have further questions! Let’s dive in.
July 2021: Ask Maddaux
Q: I know there is a lot of talk these days around the use of member data and data analytics. It all sounds so intimidating and potentially expensive. What is an easy project to dip my toes into the world of data analytics?
A: Get started by understanding current member spend in two categories: gas and groceries. Why these two retailers? Because, these two simple purchase data points provide volumes of insight about your members. For example, identifying where members shop for food, segmented by age, product usage and zip code will provide indicators of other spending habits, such as overall spend. The depth of the purchase behavior is strengthened by adding gas retailers into the analysis. Gas is a fascinating data point as it shows proximity to work or home as well as pricing threshold of value.
Through this segmentation of members by value sensitivity, many trends can begin to emerge. Members who show value-priced indicators may be more likely to respond to promotions that offer payment versus rate. May be more likely to use budgeting software and would like to know how much they have saved in fees because they bank at the credit union, not someplace else.
Another valuable insight gleaned from gas and grocery data is the potential for credit/debit card acquisition and increased usage from existing cardholders. With the knowledge of most used retailers, the credit union can offer a rewards program that can be tailored to member segments, delivering for a nearly individualized custom rewards program. While members will delight in earning points for existing behavior, this will also help secure the coveted top of wallet position, and spur increased cross-sell and up-sell opportunities. In re-acquisition efforts, identifying current competition allows for nearly individually crafted messages. A robust competitive proof point is the savings the member can achieve by moving spend behavior from a competing card to the credit union.
Have additional data analytics questions? We are here for you! Drop us a line at hello@auxteam.com