Reducing Adverse Selection through Customer Relationship Management
Yong Cao, Thomas S. Gruca
Abstract
Yong Cao, Thomas S. Gruca
Abstract
Adverse selection is an important problem for marketers. To reduce the chances of acquiring an unprofitable customer, companies may screen prospects who respond to a marketing offer. Prospects who respond are often not approved. At the same time, prospects who are likely to be approved are unlikely to respond to a given marketing offer. Using data from a firm's customer relationship management system, the authors show how to target prospects who are likely to respond and be approved. This approach increases the number of customers who are approved and reduces the number of applicants who may defect after being turned down. This method can be extended to new customer acquisition and more effective targeting of costly promotions to migrate customers to higher levels of lifetime value.
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Adverse selection is an important problem for marketers. To reduce the chances of acquiring an unprofitable customer, companies may screen prospects who respond to a marketing offer. Prospects who respond are often not approved. At the same time, prospects who are likely to be approved are unlikely to respond to a given marketing offer. Using data from a firm's customer relationship management system, the authors show how to target prospects who are likely to respond and be approved. This approach increases the number of customers who are approved and reduces the number of applicants who may defect after being turned down. This method can be extended to new customer acquisition and more effective targeting of costly promotions to migrate customers to higher levels of lifetime value.
Key concepts: Business, Marketing, Customer lifetime value, Selection (genetic algorithm), Adverse selection, Customer relationship management, Value (mathematics), Customer retention