Birds of a Feather: Using Data Science to Understand Member Behavior
Struggling with clustering your members into meaningful groups beyond Demographics? Learn how Consumers Credit Union in Illinois tackled this problem. By working with the Domo Labs AI team, CCU developed robust behavioral models. This approach focuses on how members interact with the Credit Union, rather than relying solely on common demographic characteristics or simple metrics like account balances.
Here are the key takeaways:
- Learn how behaviors can help define customer engagement.
- Understand why traditional demographics are called “Lazy” at CCU.
- How engaging at an enterprise level is critical for driving data success in your company.
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Charles Smith began his data exploration journey just over a decade ago as an analyst writing SQL queries to identify fraudulent activity. Over time, that passion for data and analytics grew, leading him to explore new opportunities in the field. With a strong foundation in problem solving and data driven decision making, Charles has since expanded his expertise, helping Consumers Credit Union harness the power of data to drive business insights and improve operational efficiency.
Russ Moore started his data career during the era of dial-up internet, floppy drive storage, and email relay services. While technology has increased the speed of data access, Russ’s dedication to using data remains unchanged. He believes that data should serve the purpose of 'solving business problems.' This principle, along with Domo, has enabled Consumers Credit Union (CCU) to achieve significant user engagement across the company. By focusing on business outcomes, CCU has recorded over 100,000 card/dashboard views among its 375 employees.
Florencia Silveira is a data scientist on Domo’s AI Labs team, where she collaborates with customers on DSML solutions and works alongside the development team. Her training focused on quantitative research approaches, statistical methodology, and data storytelling. She has worked with nonprofits, research foundations, and scholars on end-to-end projects, providing methodological expertise and support. Florencia is an avid fan of the Domo platform and everything it can accomplish—from data ingestion to dashboarding. Her favorite part of the job is the constant opportunity to combine three of her favorite activities: interacting with intelligent people, conducting intensive data deep dives, and using an easy-to-navigate data experience platform.
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