Inequality in the utility of customer data: Implications for data management and usage

Customer data has long been recognized as a critical resource for supporting marketing efforts. With the rapidly increasing investments in the acquisition and the administration of customer data, the concern about cost-effective management of this important resource is growing. In this study, we explore the concept of inequality in the utility of data- the extent to which records in large data sets differ in their business-value contribution. The Lorenz curve and the associated Gini index, powerful tools for analyzing inequality, have been applied to a variety of social and economic disciplines. We adapt these tools for modeling and measuring inequality in the context of managing large customer data sets, and use them for analyzing utility/cost trade-offs and optimizing data management decisions. We demonstrate the application of these tools in the customer relationship management context of managing alumni relations, using large data samples from a real-world system. The results support our argument that understanding and measuring inequality in the utility of data may have important implications for better usage and administration of customer data.