In one division last year we improved retention by 1%. That may not sound like much, but when the product portfolio is very large, it adds up to a lot.
Derlin Mputu Kinsa
Senior Manager, Corporate Strategy and Business Intelligence
Predictive Analytics Drives Improvements in Customer Retention
- Three years ago, the company decided to launch a customer retention program in Europe.
- Some segments of the customer base were facing some challenges with lower renewal rates.
- In devising and implementing the retention strategy, one of the major goals was that it be fact-based.
- The starting point was to understand which segments of the customer base were most affected by the lower rates of renewal, and to distill the key events that led to churn.
- Focused on improving the targeting of customers so that professionals were not offered unsuitable products.
- Before the customers show evident signs of dissatisfaction, the firm determines what offer they should make to maximize the odds of retaining them.
- Once the customers are actively using the products they have purchased, the company works proactively to determine additional product offers to maximize the lifetime value of each customer.
- In one division last year, improved retention by 1%.
- After demonstrating success in Europe, the program grew to include the United States and the scope expanded to embrace the entire customer lifecycle.
- Reshaping operations so that business managers can take advantage of the insights from analytics at critical touch points with the customer.
- Analysis of canceled subscriptions is used to shape product development and pricing strategy.