Customer attrition is a costly problem in the financial services business. With customer churn in the banking sector averaging ten to twenty percent annually-and replacement costs running from $200 to as high as $3500 and up per customer-keeping the right customers happy is essential. For some companies, as little as a five percent improvement in customer retention can increase profitability by 25 to 100 percent.
Banco Espírito Santo fights the spread of an eroding customer base with SPSS predictive analytics—identifying key behaviors of customers likely to leave the bank. By focusing retention efforts on their most valuable customers, Banco Espirito Santo reduced attrition by 15 to 20 percent and increased profits by 10 to 20 percent.
SPSS customer retention solutions help financial services firms keep the right customers longer with real-time predictive analytics. Identify the customers most likely to defect—before they end their relationship—and predict which actions will earn their loyalty. Apply predictive analytics to discover churn patterns and develop profiles of customers who have defected for a deeper understanding of why they left. Pinpoint when and why certain customers defect to identify strategies to keep them as satisfied customers.
Deploy predictive retention intelligence to customer-facing employees and systems throughout your organization to decrease customer churn in real time. Provide the early warning tellers, call center reps and other employees need to take action to keep your best customers longer and improve customer lifetime value. For example, with real-time predictive intelligence integrated within a call center application, your call center representatives have the insight they need for the best chance of keeping customers happy. Call center reps know each customer’s lifetime value, their risk of churning, and the recommendation most likely to keep the customer happy. That recommendation can even be refined in real-time—while the representative is talking to the customer—by conducting a brief “needs assessment” survey. The rep then feeds that survey data into the call center application, and a new recommendation is generated based on real-time predictive analysis.
Contact SPSS sales to learn how predictive analytics can deliver rapid return on investment for your organization.