Magazine article ABA Bank Marketing

Analytics: Your Next Best Thing to a Crystal Ball: In Today's Competitive Environment, It's Important for Banks to Maintain and Grow Customer Relationships in Order to Sustain Profitable Growth. but as Banks Continue to Attract New Customers through Acquisition, Existing-Customer Churn Undermines This Growth

Magazine article ABA Bank Marketing

Analytics: Your Next Best Thing to a Crystal Ball: In Today's Competitive Environment, It's Important for Banks to Maintain and Grow Customer Relationships in Order to Sustain Profitable Growth. but as Banks Continue to Attract New Customers through Acquisition, Existing-Customer Churn Undermines This Growth

Article excerpt

"Churn" refers to both the percentage of customers who end (heir relation with a bank and customers who still use a hank's services but not as much or as often as they used to. One of the biggest reasons for churn: Customers' needs change--often without the hank anticipating or even noticing these changes.

If banks want to prevent churn before it happens, they need to do a better job of anticipating and understanding their customers' needs. Unfortunately, banks don't have a crystal ball to help them predict customer churn. However, they have something almost as good: transactional data.

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Identify and target at-risk customers

Data, such as the number of ACH transactions, debit card usage, and number of checks written, provide banks with a rich repository of information. Data mining and analytics break down customer information to drive insights that can help identify "at-risk" customers. This proactive identification of at-risk customers combined with targeted communication can significantly reduce customer churn.

When deciding what customers to keep or grow, banks need to consider the entire banking relationship. Analytics offer a 360-degree view of customer lifetime value, so educated decisions can be made about which customer relationships are worth salvaging.

Using analytics to segment the customer base and track the history of account transactions, banks can build models to predict the likelihood of customer churn. These models rank customers on their likelihood to attrite. With that knowledge, a bank can market specifically to customers with qualifying attrition scores.

Segment customers into quadrants

When you calculate customer attrition scores with household profitability, your bank can segment its customer into four attrition-marketing quadrants (see chart). …

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