SPSS - Customers

Banco Espírito Santo (BES)

Situation

Emerging global opportunities and technology are revolutionizing the banking industry and fostering intense competition and high customer expectations. Once-loyal customers now move their assets to new banks effortlessly and with alarming frequency.

Challenge

Banco Espírito Santo (BES) fights the spread of an eroding customer base every day. As their customers gradually reduce transaction activities, they also begin diverting assets to other banks.

Solution

With PASW Modeler data mining technology from SPSS Inc., BES identifies key behaviors of customers who are likely to leave the bank. Jorge Portugal and his strategic marketing team dynamically profile these relationships and build models to test intervention tactics to keep customers happy—and keep them.

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Results

Gained access to previously unused customer behavior data
Reduced customer attrition rate by 15 to 20 percent
Increased bottom-line profits by 10 to 20 percent

Founded in 1880, BES serves more than one million customers at more than 600 branches in Portugal, 22 in Spain, and another 32 offices in 12 countries. The bank’s commitment to customer service led its strategic marketing group to articulate a clear mission: implement analytical tools and adopt relationship-building techniques to precisely predict customer behavior and increase customer loyalty. As head of the BES marketing team, Jorge Portugal wanted a powerful data mining solution to take full advantage of the information contained in their database.

Customer attrition is a progressive illness for any service business. Staying healthy and prosperous in today’s competitive financial market requires rigorous preventive measures. Portugal and his team at BES devised a threestep data mining process to maintain long-term relationships with their customers. First, they set out to identify the different categories of customers by analyzing their transaction behaviors. Building highly detailed and dynamic models—mathematical equations representing these behaviors—was the next step in their analytic process. Then the BES team plotted an intervention strategy to satisfy their customers’ needs—and keep them from going to the competition.

SPSS Inc. empowers us to know ahead of time when a customer is at risk of leaving. Now we can take the appropriate action to keep them.
Jorge Portugal
Strategic Marketing Director
BES

Gained access to previously unused customer behavior data

Portugal and his team at BES chose PASW Modeler to help their strategic marketing team analyze and model 100-gigabyte datasets. Portugal describes how they began:

“Our first step in the process was to realize that not all customers are equal. Data mining helps us focus retention efforts on our most valuable customers.”

The marketing team gathered statistics on customer behavior and customer satisfaction from every possible source, including Web logs, transactions, demographic, and third-party data. With SPSS Inc.’s data mining products, departments throughout BES use this data to better understand their customers. They quickly create and review neural net models, decision trees, and use other analytical procedures to monitor customer behavior and determine when to intervene. Then they share results immediately between marketing, sales, customer service, and other departments to identify customers at risk of leaving and take measures to keep them.

Reduced customer attrition rate by 15 to 20 percent

BES fights three basic kinds of customer loss (also known as migration). Arbitrage migration occurs when a customer with the same basic needs wants better performance and price. Product migration occurs when the customer desires higher performance or prestige from the current brand. The most serious type of customer loss is need migration, when the customer has new core needs that current products may not address. Using modeling techniques against the transaction data, Portugal and his team identified subtle variations in customer transaction behavior.

Armed with the knowledge of how customers respond to specific offers, Portugal tracks their perception of the product’s quality and their satisfaction with the service. “SPSS Inc. empowered us to know ahead of time when a customer is at risk of leaving,” he said. “Now we can take the appropriate action to keep them.” With this solution, the team was able to reduce customer asset erosion 15 to 20 percent by refining the BES product line and service offerings, by improving transactional issues like checking account and customer information management, and by reviewing personal advising procedures.

Increased bottom-line profits by 10 to 20 percent

Before using PASW Modeler, BES had never been able to tackle its customer retention problem effectively. But after identifying and modeling the behavior of potentially migrating customers, they can take proper action to retain those customers. For example, after reviewing a report that highlighted a customer who was making advance payments on her individual credit account, a BES branch manager called her to ask about it. As part of the retention strategy indicated during analysis, the manager also asked about her general perceptions of BES products and services. The customer shared her dissatisfaction with the product—compared with what she heard about competitive ones—and described some negative experiences with service. After specifically refuting the competitor’s claims, the manager worked with this customer to adjust her service and meet her personal needs. BES retained her long-term business because it had analyzed her needs and addressed them specifically. By spending time with important customers, BES is increased bottom-line profits by 10 to 20 percent in a single year.