Data‐Driven Approaches to Targeting Promotion E‐mails: The Case of Delayed Incentives

This paper empirically investigates using the e‐mail channel to target customers with a delayed incentive promotion—specifically, gift card promotion—and derives data‐driven e‐mail targeting policies. Gift card promotions are popular across retailers because they incentivize customers to spend more than a fixed expenditure level on regularly priced products by rewarding customers with a gift card to be redeemed against a future purchase. The e‐mail channel provides retailers with new sources of customer‐level data, which enables better prediction of customers' responsiveness to e‐mails (e.g., clicking) and the sales promotion that comes with it (e.g., participation in the promotion). We formulate the retailer's promotion e‐mail targeting problem by maximizing two objectives—the promotion's profitability (i.e., profit‐based targeting) and e‐mail click‐through rate (i.e., CTR‐based targeting). We also take into account the retailer's promotion budget and exclusivity concerns in targeting e‐mails. We use a comprehensive dataset from a Fortune 500 luxury fashion retailer's online channel and utilize both parametric and non‐parametric methods to predict customers' response to promotion e‐mails. Our data‐driven targeting policies improve the promotion's profitability by 5.57% and e‐mail CTR by 472.57%, on average, compared to our partner retailer's current e‐mail policy. We also find that the CTR‐based targeting policy lowers the promotion profitability by, on average, 9.09% compared to the profit‐based one. However, the CTR‐based policy recuperates the short‐term losses in the long‐term and increases the long‐term profitability by 3.94%, on average, compared to the profit‐based targeting policy.