Optimizing time limits in retail promotions: an email application

Abstract

Most marketing managers know intuitively that once a customer delays a purchase decision, the potential is high that the purchase may be put off indefinitely. In response, marketing managers usually set 'deadlines' or time limits for how long an offer is available. However, research has shown that, while time limits can help motivate customers to buy now rather than later (or not at all), time limits that are over/under restrictive may actually hurt response more than help. We consider two opposing forces of time, namely awareness and urgency. Longer time limits allow for greater awareness of an offer, which, everything else being equal, should lead to a larger response. At the same time, longer time limits also reduce the urgency of an offer leading consumers to delay their purchase (perhaps) indefinitely and thus, everything else being equal, lead to a lower response. Using decision calculus, we model the optimal time limit for promotional offers and demonstrate its use in an email marketing application. Email marketing has emerged as a profitable tool for companies like Amazon and JCrew who regularly use email to communicate promotional offers to their customers because of its low cost to implement and its relatively high response rates. This research contributes to the field by providing marketing managers a methodology for determining superior choices for time limit in promotional offers.

Optimizing time limits for maximum sales response in Internet shopping promotions

“…The urgency force indicates that the promotional information will encourage the buyers to purchase the product now rather than later. These forces are similar to those observed by Hanna, Berger, and Abendroth (2005) in an email promotion. How to balance these two forces and find an appropriate time limit is an important issue for online marketing managers.…”

“…In other words, awareness increases with an increasing rate and urgency decreases with an increasing rate; but, after the reflection point, awareness increases at a decreasing rate and urgency decreases at a decreasing rate. We note that assumptions 4-7 are similar to those of Hanna et al (2005) (in an email promotion), who modeled awareness only as a concave function and urgency only as a convex function. Our awareness and urgency functions agree more with real-world situations (explained in detail below).…”

“…Blattberg and Neslin (1990) pointed out that a lack of urgency will reduce the response. Hanna et al (2005) explicitly modeled the urgency of an offer. As in Hanna et al, let U(t) be the proportion of those aware that are retained due to urgency (i.e.…”

“…We first conduct the sensitivity of t* and P* to A(t) and U(t), as the functions change with the input values of A(t = 4) and U(t = 4) while holding z = 0.99 and w = 0.01. Unlike Hanna et al (2005), we have more variable A(t) and U(t) values (ranging from 0.10 to 0.90). As we see from Table 1, the optimal time limit t* decreases as A(t) increases or U(t) decreases, which agree with our intuition and Hanna et al The optimal t* varies from 2.9 to 5.1 days.…”

“…All of the above researches rarely explore the issue of setting the time limit for a product promoted in Internet shopping. Hanna et al (2005) first addressed the issue of the optimal time limit or deadline in an email marketing application. They identified two opposing forces of an email promotional offer: awareness and urgency, and used a simple exponential function to model these two forces.…”