Asymmetric Store Positioning and Promotional Advertising Strategies: Theory and Evidence
Authors: Rajiv Surendra , Dutta Shantanu , Dhar Sanjay K. 
Published: December 2003

Asymmetrically positioned retailers, who vary in the quality/in-store service offered, are increasingly using promotional advertising—the practice of advertising sale prices on familiar merchandise lines—to compete for customers who are willing to comparison shop. The objective of this paper is to examine the role of promotional advertising for stores that vary in their quality positioning in competing for customers using a game-theoretic model. Our focus is on two key retail promotional advertising decisions: the frequency with which to advertise price reductions and the accompanying depth of discount.

We consider a stylized duopolistic retail market with the two stores that differ in their service positioning. We assume that each store enjoys a relative advantage in serving a subset or segment of customers who regularly visit it and whom we call “patrons” of the store. We assume that it costs more to shop at the less-frequented store. We further assume that consumers are only partially informed about the prevailing retail prices—while they perfectly know the posted price at the store that they patronize, they are uncertain about the price at the other store and have rational expectations about these prices. Consumers in this market differ on three dimensions: preference for service, shopping costs, and store switching costs. We explicitly consider two consumer segments differing in their willingness to pay for service. Furthermore, we assume store switching is more costly for the high-valuation segment. We allow for within-segment heterogeneity by assuming that consumers differ in their shopping costs.

Our analysis shows that if promotional advertising is not “too costly,” the equilibrium strategies of the competing retailers entail occasionally posting its “regular” price but not advertising that price and on other occasions posting its “sale” price and advertising that price. The analysis also suggests that promotional advertising is driven by “offensive” (traffic-building) as well as “defensive” (consumer-retention) considerations. Furthermore, the relative importance of offensive and defensive considerations is influenced by the service positioning of the stores. Specifically, relative to the low-service store, promotional advertising by the high-service store is driven more by offensive consideration than defensive consideration. Finally, a store's service positioning impacts its frequency of promotional advertising and the depth of discount that it offers during “sale.” Specifically, relative to the low-service store, the high-service store offers advertised sales more frequently but with shallower discounts.

These results follow from the fact that differences in service positioning lead to a natural consumer “self-selection.” Specifically, the consumer-mix of the high-service store comprises a higher fraction of the high-valuation consumers who are less sensitive to promotional advertising due to their higher store switching costs. Thus, if the low-service retailer were to build store traffic by targeting the customer mix of the high-service retailer (motivated by offensive consideration), it has to offer deeper discounts; yet the demand enhancement is lower. Thus, relative to the high-service store, promotional advertising is not that attractive for the low-service store. However, the low-service store still relies on offering discounted prices occasionally to retain its customer base. Thus when using promotional advertising to attract and retain customers, the high-service store should rely more on the “frequency cue,” while the low-quality store should rely more on the “magnitude cue.”

We provide empirical support for the key predictions of our analytical model by collecting and analyzing retail promotional advertisements for stores that vary in their level of in-store service, published in major newspapers in a large U.S. metropolitan city. We collected data from 813 advertisements across 14 different product groups in the men’s and women's categories. The data are consistent with the model's predictions. Our theory and empirical analysis should be of interest to both academics and practitioners, particularly those in the area of channel management and promotional advertising.