The Effectiveness of Customized Promotions in Online and Offline Stores
Published 4/1/2009
Author: JIE ZHANG and MICHEL WEDEL
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Executive Summary
The development of innovative technologies has brought unprecedented opportunities for improving promotion effectiveness through customization in both online and offline stores. Yet it is unclear what the ideal level of customization is in each channel. Is customization always a case of “the finer, the better”? What is the more suitable channel for individual-level customized promotions? In this study, the authors provide insights to help answer these questions by empirically examining the profit potential of various customized price promotions at different levels of granularity in online and offline channels. They compare “competitive promotions,” defined as promotions aimed at consumers who did not purchase the target brand on the previous purchase occasion, and “loyalty promotions,” defined as those aimed at consumers who purchased the target brand on the previous purchase occasion. They also distinguish three levels of customizations: First, a mass market–level customized promotion offers the same amount of price discount to all relevant consumers (i.e., buyers or nonbuyers on the previous purchase occasion). Currently, this is the most common type of customized price promotions in practice. Second, a segment-level promotion customizes the depth and frequency of the price discount to each segment of relevant consumers, but it is not further tailored toward individuals within a segment. Third, an individual-level promotion is defined as one that is personalized for each consumer. This type of promotion represents customer-centric marketing at the most granular level.
The authors conduct their analyses with a joint model of purchase incidence, choice, and quantity, as well as a series of optimization procedures that derive profit-maximizing price promotions using purchase data from a matching sample of online and offline stores. They compare the expected profit of various promotion programs across approximately 300 conditions. The key findings are as follows:
- Optimization procedures lead to substantial profit improvements over the current practice for all types of promotions, including customized and undifferentiated promotions.
- Loyalty promotions are more profitable in online stores than in offline stores, while the opposite holds for competitive promotions.
- The incremental profit of individual-level promotions over segment-level promotions and of segment-level promotions over mass market–level customized promotions is small in general, especially in offline stores in which the differences are less than 1% on average.
- For categories that are promotion sensitive, firms can gain meaningful profit increases from individual-level over segment-level customized promotions and from segment-level over mass market–level customized promotions in online stores. If individual-level promotions are to be implemented, the Internet would be the more suitable channel.
- Low redemption rates are a major impediment to the success of customized promotions in offline stores. Optimal undifferentiated promotions should be the primary promotion program in this channel, and firms can benefit from offering a combination of optimal undifferentiated and customized promotions for suitable categories in offline stores.
Biography
Jie Zhang is Assistant Professor of Marketing and Harvey Sanders Fellow of Retail Management in the Robert H. Smith School of Business at the University of Maryland. She obtained her PhD in Marketing from the Kellogg Graduate School of Management at Northwestern University. Her general research interest is to apply econometric and statistical models to study consumers’ purchase behavior and response to various promotion programs and then to design innovative decision support tools for marketers based on these models. She is particularly interested in their applications in the Internet shopping environment. Her recent research projects focus on online promotion customizations and shopping behavior, as well as various topics that aim at improving decision making for retail management in general. Her research has won the Procter & Gamble Marketing Innovation Research Award and has been sponsored by the Marketing Science Institute. She has published articles in leading marketing and management journals, such as Marketing Science, the Journal of Marketing Research, and Management Science.
Michel Wedel is PepsiCo Professor of Consumer Science in the Robert H. Smith School of Business at the University of Maryland. His main research interest is in consumer science—specifically, the application of statistical and econometric methods to further the understanding of consumer behavior and to improve marketing decision making. He has won the Hendrik Muller lifetime award for the social and behavioral sciences awarded by the Royal Netherlands Academy of Sciences for “exceptional achievements in the area of the behavioral and social sciences” and has been elected as a foreign correspondent of that academy. He has also won the O’Dell Award for best article published in Journal of Marketing Research. He has published more than 150 articles in peer-reviewed journals and has received more than 2000 total citations. He was ranked Number 1 among all scholars in economics and business in the Netherlands. He has supervised 12 doctoral students; serves on the editorial boards of Journal of Classification, Quantitative Marketing and Economics, and Journal of Marketing; and is an area editor for Marketing Science and an associate editor for Journal of Marketing Research. He has also published books on market segmentation, models for marketing decisions, and visual marketing.
J Marketing Research, Volume 46, Number 2, April 2009
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