Many retailers have collected large amounts of customer data using, for example, loyalty
programs. We provide an overview of the extant literature on customer relationship …

In this paper, quantitative models for direct marketing models are reviewed from a systems
perspective. A systems view consists of input, processing, and output and the six key …

In recent years, deep generative models have been shown to'imagine'convincing high-
dimensional observations such as images, audio, and even video, learning directly from raw …

The need to understand the relationships among customer metrics and profitability has
never been more critical. These relationships are pivotal to tracking and justifying firms' …

We document the hidden costs of a popular nudge and show how these costs distort policy
making when neglected. In a field experiment with a charity, we find reminders increasing …

In this paper we propose a robust formulation for discrete time dynamic programming (DP).
The objective of the robust formulation is to systematically mitigate the sensitivity of the DP …

A basic yet crucial question is: why should the firm engage in database marketing? We
discuss three fundamental motivations: enhancing marketing productivity, creating and …

There is now an extensive theoretical literature investigating optimal inventory policies for
retailers. Yet several recent reviews have recognized that these models are rarely applied in …

In predictive modeling, firms often deal with high-dimensional data that span multiple
channels, websites, demographics, purchase types, and product categories. Traditional …

Planning problems that involve learning a policy from a single training set of finite horizon
trajectories arise in both social science and medical fields. We consider Q-learning with …