Regional financial services company, Bremer Bank, provides financial services offerings including banking, insurance and investment management, and wanted to improve customer experience to increase customer satisfaction. They used Zaloni’s Arena DataOps platform to build golden customer records that uncovered cross-sell and upsell opportunities to drive top-line growth and increase customer lifetime value.
Challenge: Bremer Bank was modernizing their technology systems and wanted to centralize siloed data across their lines of business. Due to their organizational focus on customer experience, they needed to integrate all customer data sets to create trusted golden records of their customers that could be leveraged and synchronized across their five lines of business. The company faced challenges matching and mastering data from various systems and sources including internal, external and 3rd party data sources including EPIC, Raymond James and internal CRM systems. Many of the data sets lacked unique identifiers and had critical fields missing creating integration and enrichment challenges.
Solution: Arena allowed the company to architect a cloud-based data lake. The lake was hydrated with an initial set of data sources to understand data set structures, requirements and what the end result or golden customer records should be, then the solution was built using Arena’s data mastering to put customer golden record creation into production. Arena’s data mastering is powered by a machine learning engine and data mastering continuously improves over time as new data sets are added. Using Arena, the company was able to build a data science workbench to help data scientists to uncover new data monetization opportunities.
Results: Arena enabled Bremer Bank to build golden customer records that are leveraged by sales, marketing and customer success to improve customer experience, provide personalized marketing offers and increase revenue by uncovering cross-sell and upsell opportunities. Arena saved 8 hours/day of data engineering work, reducing costs and improving efficiency. The data science group was able to uncover new data monetization opportunities through the workbench capabilities within the platform.