Dynamically Managing a Profitable Email Marketing Program

TLDR

Email marketing is highly profitable and widely used, yet research has mainly examined either customer email responses or average purchase effects, leaving a gap in understanding. The study aims to analyze customers’ email open and purchase behaviors using a unified hidden Markov and copula framework and to develop a decision support system that guides retailers toward optimal email contact decisions. The authors employ a unified hidden Markov and copula model on retailer data and conduct a counterfactual analysis to evaluate email contact strategies. The study reveals that email activity does not predict purchase activity, that email volume has a nonlinear impact on profitability, and that deviating from the optimal seven emails can reduce lifetime profit by up to 32%.

Abstract

Although email marketing is highly profitable and widely used by marketers, it has received limited attention in the marketing literature. Extant research has focused on either customers’ email responses or the “average” effect of emails on purchases. In this article, the authors use data from a U.S. home improvement retailer to study customers’ email open and purchase behaviors by using a unified hidden Markov and copula framework. Contrary to conventional wisdom, the authors find that email-active customers are not necessarily active in purchases, and vice versa. Furthermore, the number of emails sent by the retailer has a nonlinear effect on both the retailer's short- and long-term profitability. Through a counterfactual study, the authors provide a decision support system to guide retailers in making optimal email contact decisions. This study shows that sending the right number of emails is vital for long-term profitability. For example, sending four (ten) emails instead of the optimal number of seven emails can cause the retailer to lose 32% (16%) of its lifetime profit per customer.