Overcoming the recency trap in customer relationship management

Purchase likelihood typically declines as the length of time since the customer's previous purchase (recency) increases. As a result, firms face a recency trap, whereby recency increases for customers who do not purchase in a given period, making it even less likely they will purchase in the next period. Eventually the customer is effectively lost to the firm. We develop and illustrate a modeling approach to target a firm's marketing efforts, keeping in mind the customer's recency state. This requires an empirical model that predicts purchase likelihood as a function of recency and marketing, and a dynamic optimization that prescribes the most profitable way to target customers. In our application we find that customers' purchase likelihoods as well as response to marketing depend on recency. These results are used to show that the targeting of email and direct mail should depend on the customer's recency and that the optimal decision policy enables the average high recency customer, who currently is virtually worthless to the firm, to become profitable.