The Client, an international NGO, is confronted with significant churn of their established base of direct debit customers.
The client wanted to predict which of their customers are most likely to churn and thereby proactively retain customers and increase Customer Lifetime Value.
The risk of waking a dormant customer (a customer who wouldn’t churn) is just as costly for the Client as not contacting a churning customer. It might have the opposite effect of pushing the customer to churn. Therefore the precision of identifying customers who are most likely to churn was critical.
Using existing data from the Clients system, purchased services, activity and responses to previous marketing efforts, One Prediction predicts each individual customer’s probability to churn. This enables the retention team to focus their resources on the customers most at risk and offer them incentives to remain loyal.
The churn model was built a few days after uploading customers’ data. The Client was able to evaluate the model results retroactively: “Was One Prediction able to predict which customers actually churned historically”.
The client now has a tool to identify on an ongoing basis, which customers to prioritize in a “I love you” call. The Client is also defining how many clients to call to maximize the ROI of the activity, based on One Prediction’s “profit curve”.