Models of Customer Behavior: From Populations to Individuals

Abstract

There have been various claims made in the marketing community about the benefits of 1-to-1 marketing versus traditional customer segmentation approaches and how much they can improve understanding of customer behavior. However, few rigorous studies exist that systematically compare these approaches. In this paper, we conducted such a systematic study and compared the performance of aggregate, segmentation, and 1-to-1 marketing approaches across a broad range of experimental settings such as multiple segmentation levels, multiple real world marketing datasets, multiple dependent variables, different types of classifiers, different segmentation techniques, and different predictive measures. Our results show that, overall, 1-to-1 modeling significantly outperforms the aggregate approach among high-volume customers and is never worse than aggregate approach among low-volume customers in our experimental settings. Moreover, the best segmentation techniques tend to outperform 1-to-1 modeling among low-volume customers.