Abstract
This paper discusses the interaction between revenue management (RM) and customer relationship management (CRM) for a firm that operates in a customer retention situation but faces limited capacity. We present a dynamic programming model for how the firm balances investments in customer acquisition and retention, as well as retention across multiple customer types. We characterize the optimal policy and discuss how the policy changes depending on capacity limitations. We then contrast the modeling results with those of a behavioral experiment in which subjects acted as managers making acquisition and retention decisions. In the modeling part of the paper we introduce a new concept, the value of an incremental customer (VIC), and show that regardless of capacity limitation the firm selects acquisition and retention spending such that the cost of acquiring/retaining a customer equals his/her VIC. When capacity is unlimited VIC equals customer lifetime value (CLV), but when capacity is limited it is much smaller and changes dynamically depending on the number of customers and their mix. As a result the optimal spending is constant and depends on CLV for the firms with unlimited capacity, but changes dynamically and is generally unrelated to CLV when capacity is limited. In the experimental part we introduce a concept of conditional optimality and discuss its applicability to the analysis of state-dependent decisions. Applying this concept to our data we document a number of decision biases, specifically the subjects' tendency to overspend on retaining high-value customers and underspend on lower-value customers retention and acquisition. Understanding these biases and the optimal policy can help firms better manage their revenues and customer relationships.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have