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Indiana University Teaching Excellence Recognition Award, 1999, 2000
Awarded Patent No. 6,604,681 ("Evaluative Shopping Assistant System") with Co-inventors Avanti Lalwani (Kelley MBA Class of 2003) and John Thong (Kelley MBA Class of 2000); Issue Date: August 12th, 2003
Awarded Patent No. 5,848,399 ("Computer System for Allowing a Consumer to Purchase Packaged Goods at Home"); Issue Date: December 8, 1998 (See also patents 6,026,377 and 6,304,855)
Charles G. Thalhimer Scholar-in-Residence, Virginia Commonwealth University, Richmond, 1998
Awarded the Journal of Consumer Research's Robert Ferber Award, 1989
Received the Kraft Award for Marketing Excellence, 1988
Awarded the American Psychological Association Division 23 Dissertation Award, 1985
Graduated Summa Cum Laude, University of Miami, 1977
Chen, M., Burke, R. R., Hui, S. K., and Leykin, A. (2021). Understanding Lateral and Vertical Biases in Point-of-Purchase Product Considerations: An In-Store Ambulatory Eye-Tracking Study. Journal of Marketing Research, 58(6), 1120-1141. View Full Text
Given the conventional wisdom that “unseen is unsold,” retail practitioners are keenly interested in understanding consumers’ attention to products in the store. Using in-store ambulatory eye-tracking, we investigate the extent to which lateral and vertical biases drive consumers' attention in a grocery store environment. Our dataset offers a complete picture of not only where the shopper is located, but also the shopper’s field of view and visual fixations during the trip. Using our novel dataset, we address two research questions: First, do shoppers have a higher propensity to pay attention to products on their left or right side as they traverse an aisle (i.e., is the right side the “right side”)? Second, do shoppers tend to pay more attention to products at their eye level (i.e., is eye-level “buy-level”)? We utilize the exogenous variations in the direction by which shoppers traverse an aisle (northward vs southward), obtainable from their shopping paths, to identify lateral bias. The exogenous variation of shoppers' eye-level positions, due to their differences in height, is used to identify vertical bias. We find that shoppers pay more attention to products on their right side when traversing an aisle, and this bias holds for both right- and left-handed shoppers. Contrary to many practitioners’ belief, we find that eye-level is not “buy-level”; rather, the product level that has the highest propensity to capture shoppers’ attention is about 14.7 inches below eye-level (which is around chest level). Further, this vertical bias becomes more prominent during the latter part of a shopping trip.
Zhang, X., Li, S., and Burke, R. R. (2018). Modeling the Effects of Dynamic Group Influence on Shopper Zone Choice, Purchase Conversion and Spending. Journal of the Academy of Marketing Science, 46(6), 1089–1107.
In many retail contexts, social interaction plays an important role in the shopping process. We propose a three-stage dynamic linear model that captures the influence of group discussion on shopper behavior within a hierarchical Bayes framework. The model is tested using a video tracking and transaction dataset from a specialty apparel store. The research reveals that group conversations have a significant impact on the shopper’s department or Bzone choice, purchase likelihood, and spending over time. This group influence is magnified by the size of the group (particularly for zone penetration and purchase conversion), and is also moderated by group composition and cohesiveness. The conversations of mixed-age groups and groups who stay together while shopping have a significant influence on shopper behavior across all three stages, while discussions by adult groups exhibit a marginal carryover effect for purchase conversion. When shoppers have repeated discussions in a specific department, they are more likely to return to and buy from this department, while the cumulative number of discussions in the store drives higher spending levels. We also observe that group shoppers visit more departments than their solo counterparts; and mixed-age groups and solo shoppers are more likely to buy than adults-only or teen groups. This study has important implications for how retailers manage shopper engagement and group interaction in their stores.
Burke, R. R. and Leykin, A. (2014). Identifying the Drivers of Shopper Attention, Engagement, and Purchase. In Dhruv Grewal, Anne L. Roggeveen, and Jens Norfalt, (eds.), Shopper Marketing and the Role of In-store Marketing, Review of Marketing Research, 11, 147-187. Bingley, UK: Emerald Group Publishing Limited.
To cope with the complexity of modern retail stores and personal time constraints, shoppers must be selective in processing information. During a typical shopping trip, they visit only a fraction of a store’s departments and categories, examine a small subset of the available products, and often make selections in just a few seconds. New research techniques can help marketers understand how customers allocate their attention and assess the impact of in-store factors on shopper behavior. This chapter summarizes studies using observational research, virtual reality simulations, and eye tracking to identify the drivers of shopper attention, product engagement, and purchase conversion. These include shopper goals; product assortment, package appearance, price, and merchandising; shelf space allocation, organization, and adjacencies; and salesperson interaction. The research reveals that small changes in a product’s appearance and presentation can have a powerful impact on consideration and choice.
Zhang, X., Li, S., Burke, R. R., and Leykin, A. (2014). An Examination of Social Influence on Shopper Behavior Using Video Tracking Data. Journal of Marketing, 78(5), 24-41.
Burke, R. R. (2009). Behavioral Effects of Digital Signage. Journal of Advertising Research, 49(2), 180-185.
Burke, R. R. (2006). The Third Wave of Marketing Intelligence. In Manfred Krafft and Murali Mantrala (eds.), Retailing in the 21st Century: Current and Future Trends, 113-125. Springer.
Recent innovations in the real-time tracking of customer behavior in retail stores allow marketers to measure consumer response to the in-store environment and manage the shopping process. This chapter reviews the genesis of customer experience management, describes available tools for tracking shopper behavior and measuring store performance, and discusses two case studies which illustrate the use of tracking research in retail settings. The paper concludes with a discussion of the challenges in conducting computer-based observational research and future directions.
Burke, R. R. (2005). Retail Shoppability: A Measure of the World's Best Stores. In Future Retail Now: 40 of the World's Best Stores, 206-219. Washington, DC: Retail Industry Leaders Association.
The ultimate goal of retailing is to bring together supply and demand; to provide consumers with a selection of goods and services that satisfy their needs profitably. While manufacturers and retailers have made considerable progress on managing the supply side, the news is not as good on the demand side. Merchants continue to have difficulty creating shopping environments that engage consumers' needs and convert these desires to purchases. Deficiencies in the shopping environment have produced high levels of consumer stress and reduced shopping frequency and purchase conversion rates.
This article introduces the concept of retail shoppability: the capacity of the shopping environment to transform consumer needs and desires into purchases. Using examples from a global study of best practices in retailing, the paper presents a set of 10 principles that can help manufacturers and retailers improve the shoppability of their stores, leading to increased sales and customer loyalty. The paper discusses research tools that managers can use to measure the quality of the customer shopping experience and pinpoint areas in need of improvement. These include conventional techniques, such as store audits and customer surveys, as well as more sophisticated, technology-based approaches, including using virtual reality simulations of the store environment to test new concepts, and video cameras and other location sensing devices to track customer shopping patterns. The paper concludes with a discussion of future trends in customer experience management.
Burke, R. R. (2002). Technology and the Customer Interface: What Consumers Want in the Physical and Virtual Store. Journal of the Academy of Marketing Science, 30(4), 411-432.
For companies to realize the benefits of recent innovations in customer interface technology, they need to understand the value consumers place on technology as part of the shopping process. A national survey of 2,120 online consumers was conducted to explore how people want to shop in both online and in-store environments and determine how interactive and conventional media work together to move consumers through the purchase process. The study investigated 128 different aspects of the shopping experience, from common elements to recent innovations. The results indicated that consumers are generally satisfied with the convenience, quality, selection, and value provided by retailers today. They are less satisfied with the level of service provided, the availability of product information, and the speed of the shopping process. The findings suggest that new technologies can enhance the shopping experience, but applications must be tailored to the unique requirements of consumer segments and product categories.
Burke, R. R., Rangaswamy, A., and Gupta, S. (2001). Rethinking Marketing Research in the Digital Age. In Jerry Wind and Vijay Mahajan (eds.), Digital Marketing: Global Strategies from the World's Leading Experts, 226-255. New York, NY: John Wiley & Sons.
In the past few years, digital technologies have stimulated several innovations in marketing research, including online survey methods and focus groups, e-commerce customer tracking systems, data mining tools, and 3D graphic simulations. Technology is changing the way marketing data are collected, analyzed, and used to support managerial decisions. This article provides an overview of these innovations, discusses their benefits and limitations, and explores how these developments will alter the nature and scope of the marketing research function in the future.
Burke, R. R. (1996). Virtual Shopping: Breakthrough in Marketing Research. Harvard Business Review, 74(March-April), 120-131.
Virtual reality simulations provide an efficient, flexible, and reliable method for recreating the in-store shopping experience and measuring consumers' reactions to new marketing concepts. In this pioneering article, Dr. Burke describes the process of building virtual shopping simulations, validating the methodology, and applying the tool to several marketing problems, including measuring brand equity, managing product category assortments, and organizing shelf displays.