CASE STUDY

Churn Prediction and Customer Retention Analytics Deliver an 85% Reduction in Customer Churn for a Multinational Bank

Sep 22, 2016

Business Challenge

Reducing customer churn and improving customer retention

A leading multinational private bank wanted to understand the cause for high churn from its corporate clientele in the UK market, and improve customer retention.

Situation: 

High customer attrition within few months of partnering

The client was facing high churn with its corporate accounts. The clients were applying for cancellation of accounts within a few months of partnering with the bank. Due the high cost of customer acquisition, the bank was incurring considerable losses. The client wanted to decrease attrition and improve customer retention, in order to generate profits.

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Solution/Approach: 

Retention and churn modeling on the customer transaction and behavior data

We used retention and churn modeling on the customer transaction and behavior data, in order to identify patterns in customer attrition, and discern the causes for customer defection. We also used predictive analytics for churn prediction to identify clients most likely to cancel partnerships, and suggested remedial actions.

Impact

85% reduction in attrition and 12% improvement in ROI

The client was able to identify the accounts with highest profit potential, and most likely to defect. Client developed targeted customer retention strategies which improved the overall customer experience, and was able to reduce attrition by 85%, and increase ROI by 12%.

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