Case Study: STCU Improves Customer Communication and Reporting with Data Integration Solution
A credit union finds that bringing together information from disparate systems into a single environment helped it create better reports and enhance customer service.
- By Rozalind Kitt
- March 31, 2009
by Rozalind Kitt
Established in 1934, STCU is the Inland Northwest’s largest and most successful credit union. With more than $1 billion in assets, STCU has more than 339 employees serving 74,000 members through 12 branch locations. It is a full-service financial institution, with investment accounts, business services, and an abundance of member services.
STCU belongs to a technology consortium of regional credit unions. Several years ago, the consortium began to explore data warehousing solutions to facilitate reporting and analysis for its organizations. A comprehensive data warehousing solution was designed to bring all the information that resided in disparate systems into one environment -- allowing us to create better reports and to enhance customer service. The consortium considered several solutions, including offerings from Microstrategy and IBM. However, we were most impressed by Pitney Bowes Group 1 Software’s Data Flow, as it met all of our criteria for an ideal data integration and business intelligence solution -- robust and user-friendly features, easy installation, and good value.
Prior to implementing Data Flow, our customer information resided in separate silos. We could not produce a single view of the customer, and there was no way to track customer preferences within a single application that could be easily accessed across the enterprise. In conjunction with Data Flow, we were able to build a custom “Conversation Engine,” which functions as our member relationship management (MRM) system. Our in-house IT team developed the front-end engine to grab information from Data Flow and push it out to a Web application, which creates scripts that frontline service staff can use to sell different products and services.
For example, the Conversation Engine can indicate if a member is pre-approved for a loan and also alert the member service representative (MSR) about a member’s birthday. Users are able to input feedback directly into the engine based on customer response, so that it continues to build a greater knowledge base over time.
We are also able to catalog more detailed, current, and relevant information on customer records. As a result, staff members can have more intelligent interactions with customers by incorporating customer profiles, data, and preferences when transactions are initiated. Data Flow makes it easy to personalize customer mailings. The Conversation Engine is able to present very personalized messaging points, which is extremely beneficial to the tellers and front-line personnel. By leveraging data as part of the critical decision-making process, we are able to make more sophisticated and accurate choices in day-to-day business planning, as well as long-term strategy.
On the marketing side, we’ve leveraged the data warehouse to produce smarter models of member profitability. Data Flow is the front-end number cruncher for our branch location strategy. For our accounting department, DataFlow is a business-critical solution, as anyone within the organization can access the reports generated by the solution.
Currently, we have completed two projects around the Conversation Engine. Phase I began in January 2007 and was completed in July 2007. It included 16 project resources, including seven in software development. Two of the operational resources were branch personnel that represented a pilot branch of approximately 25 employees (tellers, MSRs, and branch management). Phase II was similar in nature, although we only used four software development resources and marketing was not involved because the design was already established. In Phase II, which began in April 2008 and officially completed in September 2008, we logged 1,507 hours across all resources.
We are exploring new uses for DataFlow and our Conversation Engine. Dale Davaz, director of online media and product development, is working on a project that will leverage warehouse data to help determine our credit union members’ price sensitivity (i.e., how many members will sign up if interest rates are lowered by X percent). Data Flow allows us to model based on real data, which provides much greater accuracy than relying on hunches alone.
We are excited by the possibilities that data intelligence can provide to help improve our business strategy and remain competitive in the market. An enhancement that we may consider for future phases is the ability to link the rates page to conversations that deal with account rates, loan rates, or dividend rates. Additionally, it would be beneficial to the front line and call center to have access to all the correspondence sent out by the credit union. Our core Conversation Engine users are tellers, MSRs, and phone center personnel, but we are also using the tool for product incentive tracking and may look at expanding our audience to include back office support.
Data Flow was easy to install and Pitney Bowes Group 1 Software provided onsite support for two weeks to help us get started. The overall success of this project can be measured by the fact that since June 2007, we have experienced an increase in staff referrals by more than 280 percent as a result of our improved customer relationship management tools. In the first full month of operation following the completion of Phase II (September 2008), we processed 13,633 discussions with our members. This includes referrals, “feel-good conversations” (birthday greetings, etc.) and service offerings.
We have gathered a few pointers from this project experience that should help us to be even more efficient in future phases. As the data warehouse administrator, I could have benefitted from more involvement in what our software development team was working on and changing so that I could easily build those changes into the data warehouse. In building out the reporting aspects for the Conversation Engine, it would have been helpful to have greater input at the beginning of the project from branch managers to determine their reporting needs.
Data Flow continues to impress us. It is a very powerful solution that can provide sophisticated results from users with intermediate-level skills. By leveraging data to enhance our decision making, we feel secure that we are ahead of the curve in going beyond the hunches. Ultimately, it is our commitment to customer loyalty and retention that helps differentiate STCU in a competitive market and create lasting customer bonds.
Rozalind Kitt is a data warehouse administrator at the Spokane Teachers Credit Union.