Managing Churn to Maximize Profits
56 Pages Posted: 9 May 2017
Date Written: May 8, 2017
Customer defection threatens many industries. To tackle defection, companies are developing sophisticated churn management strategies that involve two steps: estimating the churn propensity of each customer and their response to retention actions, and based on it, optimizing the retention campaign by offering incentives to the subset of customers who is expected to generate the highest lift in profit. While this approach focuses on the profitability of retention actions in its second step, rather than solely on churn, the estimation step essentially aims at maximizing the correct classification of churners and non-churners, not their expected profit lift.
In this paper, we show that using a profit-based loss function in the first stage can significantly improve the overall profitability of retention campaigns. Effectively, it ensures that high-profit customers’ churn is predicted more accurately than that of low-profit customers. In our empirical application, we find that using this new loss function can lead, on average, to a 62% increase in profit lift with no additional implementation cost. For a company like Verizon Wireless, this would translate into millions of US dollars of additional profits per retention campaign.
Keywords: Churn Prediction, Loss Function, Profit Lift, Stochastic Gradient Boosting.
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