Get Inspired Preventing Customer Churn

Preventing Customer Churn

The challenge: How to prevent customer churn

As the old saying goes, it’s easier to keep an existing customer than to get a new one. But that doesn’t mean that keeping an existing customer is easy. Customer churn is a real challenge and has significant impact on businesses. The effects of churn are long-reaching and can even jeopardize an organization’s future. In the insurance world, fierce competition and low barriers for switching are significant drivers of customer churn. Encouraging loyalty through customer relationship management is key to anticipate churn. To prevent churn and make customer service more personal, an insurance company wanted to discover how data could help them understand and predict their customers’ behavior.

How we created value: Combining business sense and machine learning to personalize service

By combining data that had never been merged before and looking at it from a different perspective, we generated new insights about the insurer’s customers’ behavior. These insights have helped them understand what makes customers who quit different from those who stay. By combining business sense with machine-learning techniques, we were able to build a model that:

■ Proactively generates a monthly list of 50 customers that have a high probability of churn
■ Indicates personalized reasons for customers that are likely to leave
■ Comes up with counter measures that could prevent the customer from leaving.

The model empowers the customer service department with the tools it needs to target churn-sensitive customers and offer them personalized incentives that could prevent them from leaving.

Better results: A radically reduced churn rate and improved customer satisfaction

Random cold-calls to measure customer satisfaction only had a 2% chance of targeting a customer that was planning on leaving. This exercise was exhausting for customer service representatives, and highly inefficient. Now that the team is able to accurately target customers who are more likely to churn, there is now a chance of 55% to get on the phone with a customer that is unsatisfied and prone to leaving. The team is now able to focus their efforts on a smaller and more targeted group of customers. This improved and personalized service leads to increased customer satisfaction and a reduced churn rate, which - in turn - will have a significant impact on profitability.

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