News Stay informed about the latest enterprise technology news and product updates.

Customer data analytics leads STCU to personalized customer service

To maintain the level of personalized customer service it was known for, Spokane Teachers Credit Union built its own customer data analytics engine to help frontline workers.

When a customer chooses to deposit hard-earned cash in a local credit union instead of a nationwide or multinational bank, the decision can usually be credited to three simple words: personalized customer service.

But as the ranks of their customers grow, credit unions often struggle to maintain the level of personalized customer service their members expect. That was the case at Spokane Teachers Credit Union (STCU), which first opened its doors to a handful of customers in 1934.

Today, that handful of customers has swelled to more than 74,000.

In 2007, to help its frontline workers improve their customer service, the credit union, which operates 12 branches in Washington state and Idaho, turned to a hybrid data integration/business intelligence (BI) platform to create a customer data analytics system it calls a "Conversation Engine," according to Rozalind Kitt, data warehouse administrator for STCU.

The platform, Pitney Bowes' Sagent Data Flow product, integrates customer data from multiple previously siloed sources within STCU's various departments, including data from the credit union's core data warehouse. The customer data includes names, addresses, how long the person has been a member, which financial products they use, and even the member's birthday.

More on customer data analytics
Read how a telecommunications data warehouse helped XO parse customer data  

Learn how Corporate Express improved customer service via 'fuzzy' search capabilities  

Find out who topped Gartner's Magic Quadrant report for customer data mining tools

 A custom engine built internally by STCU's IT department grabs the data each evening, making it available to a Web-based customer relationship management (CRM) application that its frontline workers use to interact with customers. The development and implementation took about six months, Kitt said, with the help of Pitney Bowes' consultants, who worked onsite at the credit union for much of that time.

Now, when a member calls the credit union with a question about an account, logic built into the customer data analytics engine processes that customer's personal and financial data, creates a custom script for call center representatives, and displays the information via the Web-based CRM application, Kitt said.

The engine might recognize that a customer has a large amount of money in a low-yield savings account, for example. It will quickly calculate the returns the customer could get by transferring those funds to, say, a money market account, and on the fly create a script to help the call center rep make the up-sell.

The system not only helps the bank sell its financial products, it also saves customers' time and gives them the level of personalized care they expect, Kitt said. Without the "Conversation Engine," she said, call center reps wouldn't have the tools to do their jobs.

"Instead of trying to have customers fill in something that they're probably not going to need or probably not going to use, we're trying to use logic to get them something that is going to improve their relationship with us," Kitt said.

STCU's accounting department is also using the DataFlow platform to improve its internal reporting capabilities. Marketing workers, meanwhile, tap the platform to help identify the credit union's most profitable customers and map out its strategy at a branch level, according to Dale Davaz, head of product development at STCU.

But it's the personalized care the system enables that has made STCU's investment of internal manpower and money worthwhile, according to Kitt, though she declined to say what the union paid for the DataFlow platform. Even something as simple as wishing a customer a happy birthday, which the "Conversation Engine" prompts call center reps to do, helps improve customer satisfaction, she said.

"It's the small things," she said -- "the little things like wishing someone a happy birthday that help."

Dig Deeper on Business intelligence data mining

Start the conversation

Send me notifications when other members comment.

Please create a username to comment.