Optimal Marketing Strategies for a Customer Data Intermediary

Abstract

Advances in data collection and storage technologies have given rise to the customer data intermediary (CDI), a firm that collects customer data to offer customer-specific marketing services to marketers. With widespread adoption of customer relationship management (CRM) and one-to-one (1:1) marketing, the demand for such services continues to grow. Extant empirical research using customer data for CRM and 1:1 marketing tends to have an engineering emphasis and focuses on developing analysis techniques to implement CRM and 1:1 marketing optimally (i.e., the technology for the CDI). In contrast, this article focuses on marketing strategy issues that the intermediary faces, given the availability of the technology to implement such services. Specifically, the authors develop an empirical framework to evaluate the optimal customer (exclusive/nonexclusive), product (quality or accuracy of the 1:1 customization), and pricing strategy for a CDI. They illustrate the framework for one type of CDI—a 1:1 coupon service firm that caters to grocery manufacturers—using household purchase history data from the ketchup market. The authors find that selling on a nonexclusive basis using the maximum available purchase history data is the most profitable strategy for the CDI in the particular market. They also evaluate the potential impact of retailers entering the 1:1 coupon service business. Because 1:1 marketing can increase the retailer's profits from goods sold, it is optimal for the retailer to undercut the prices of a pure-play CDI that offers 1:1 coupon services.