Nicholas H. Lurie & Charlotte H. Mason
Executive Summary
As business systems produce ever-increasing amounts of data, the challenge to extract the most value from this growing flood of information grows as well. Drawing on prior research in information technology and computer science, as well as decision making and marketing, this article presents a framework for thinking about how visual representations are likely to affect the decision processes or tasks that marketing managers and consumers commonly face, particularly those that involve the analysis or synthesis of substantial amounts of data. From this framework comes a set of testable propositions that serve as an agenda for further research.
Visualization tools have the potential to offer managers and consumers ways to improve efficiencies, reduce costs, gain new insights, make data more accessible, and increase satisfaction. At the same time the possibility for inappropriate application exists. In particular, because the raw data is "processed" to create the visual representation, biases in decision making may be accentuated. Implications of visual representations include efficiencies, cost reductions, and improved productivity; new insights; increased information accessibility and decision confidence; and potential biases.
Many visualization tools speed up routine analysis tasks by making it easier to see correlations, outliers, and trends and to make comparisons. Sales managers, assistant brand or product managers, media buyers, and others who routinely analyze large amounts of data may benefit from increased productivity that visualization tools can offer.
In addition to improved efficiencies for routine tasks, visualization tools may allow users to uncover new insights that would otherwise have gone unnoticed. Similarly, visualization tools might help marketing managers uncover formerly undetected patterns that are useful for cross-selling or up-selling.
Visualization tools that make voluminous stock and corporate bond market information more accessible to customers can lead to greater customer satisfaction and potentially to enhanced loyalty and retention. By creating an interactive and more realistic portrayal of alternatives with dynamic imaging and the ability to customize, virtual reality applications have the potential to be a win–win choice for consumers and firms.
Visual representations may also enhance biases in decision making. For example, visual representations that provide detailed views of alternatives may lead decision makers to make incorrect evaluations by considering only a portion of the data. Similarly, by increasing the evaluability of particular attributes, visual representations may lead decision makers to focus on attributes that are the easiest to compare rather than those that are the most important. More general, even seemingly innocuous decisions about color choice, orientation of shapes, and selection of markers can influence users' judgments and decisions.
Because visual representations draw on the associative, rather than the rule-based, reasoning system, their use may be best suited for situations in which hunches and intuition often lead to the same results as more systematic analysis. When intuitive approaches are likely to lead to incorrect conclusions (e.g., because of biases in interpretation), marketing managers may be better served by traditional data formats. Another approach is to encourage the use of visualization tools for exploration but to subject insights from visual representations to formal analysis.
Biography
Nicholas H. Lurie is Assistant Professor of Marketing in the College of Management at the Georgia Institute of Technology and is a cofounder of the College of Management’s BizLab (bizlab.gatech.edu), which brings together researchers from multiple business disciplines who study human behavior. He conducts research on how the information environment affects consumer and managerial decision making, including factors that affect information overload; the interaction between the information environment and decision processes; and the impact of information presentation on decision processes, outcomes, and learning. His research has been published in Journal of Consumer Research, Journal of Consumer Psychology, Journal of Retailing, Journal of Service Research, and Journal of Public Policy & Marketing. His article “Decision Making in Information Rich Environments: The Role of Information Structure” won the Ferber Award for the best article in Journal of Consumer Research based on a doctoral dissertation. He received his PhD and MS from the Haas School at the University of California at Berkeley, his MBA from the Kellogg School at Northwestern University, and his AB from Vassar College.
Charlotte H. Mason is Associate Professor of Marketing in the Kenan-Flagler Business School at the University of North Carolina at Chapel Hill. She received her BS and MS in Industrial Engineering, an MS in Statistics, and her Ph.D. in Business Administration from Stanford University. She has also taught in the Fuqua School of Business at Duke University and in the Terry College of Business at the University of Georgia. Her industry experience includes work for Procter & Gamble and Booz, Allen and Hamilton. Her current research focuses on issues related to the analysis and use of large customer databases and strategic issues surrounding customer relationship management. Her research has been published in Marketing Science, Journal of Marketing Research, Journal of Consumer Research, Marketing Letters, and Journal of the Academy of Marketing Science, and among other journals. She is coauthor (with William Perreault) of The Marketing Game!, a strategic marketing simulation.
Journal of Marketing, Vol. 71, No. 1, January 2007
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