Eye-Tracking Research for Visual Marketing

In 1924, in the first eye-movement analysis of print ads that we know of, Nixon observed eye move-ments of consumers who were paging through a magazine with print ads, while hiding himself in a box behind a curtain. Sometime later, Karslake (1940) used the Purdue Eye amera to collect eye-movement data on advertisements appearing in the Saturday Evening Post. In 1950, Fitts and his colleagues (Fitts, Jones, and Milton 1950) examined the eye movements of pilots landing an airplane, which is the first usability study that provided findings now central in Web and interface research. After a period of relative silence in marketing, new impetus for the use of eye-tracking came from Russo’s pioneering article of 1978, “Eye-Fixations Can ave the World,” in which he argued for studying eye-movements to evaluate marketing effectiveness, focusing on consumer decision processes. Russo compared five cognitive process tracing methods, including information display boards, input-output analysis, and verbal protocols, on seven criteria. The methods were rated on seven performance attributes, including quality, validity, obtrusiveness, ease of use, and cost of the equipment. He concluded that eye-fixation methodology scores high on many of these criteria and offers advantages not offered by other methods. As process tracing data, eye movements offer detail and validity. Verbal protocols were concluded to be complementary with eye fixations,no other method being more different from eye fixations, and Russo suggested simultaneous use of these two methods in marketing research.Since Russo’s article, applications of eye-tracking have appeared in substantive areas of visual marketing involving in-store choice decisions and shelf search, print advertising, TV commercials, e-commerce, labeling and educational messages, and branding. The area of visual search alone has witnessed a steep rise from a little over ten published papers per year in the early nineties to

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over two hundred a decade later. Rayner (1998) offered an extensive review of eye-tracking in reading and related areas, and Duchowski (2003) recently surveyed eye-tracking applications in various areas, including engineering and psychology, and provides a number of marketing ap-plications as well. In this paper, we review eye-movement research in marketing. We focus on broad categories of visual marketing stimuli and tasks: c

hoice and search behavior, print advertising, public policy information, television commercials, Web usability and advertising, and reading tasks in survey design and branding. The fundamental differences in the nature of the stimuli in those areas allow for unique insights in the visual attention processes in question. We specifically focus on insights on the effects of bottom-up and top-down factors on the visual attention process. We examine the insights on bottom-up space-based, feature-based, and object-based attention that these studies have afforded. We also summarize the top-down role of specific goals and tasks that consumers engage in when exposed to visual marketing stimuli, for example to select one object out of mul-tiple competing ones on a display, during search and choice, or to comprehend, evaluate, and/or memorize visual marketing stimuli as a whole, when exposed to print and television advertisements. We examine visual marketing insights gained through eye-tracking of stationary stimuli such as print ads and yellow page ads, and dynamic stimuli such as television commercials, and we explore Web usability, where consumers with multiple goals are exposed to static and dynamic scenes.

Choice and Search Behavior

In a choice or search task, the consumer’s goal is to select one out of a set of multiple objects. In a choice task, preference uncertainty needs to be reduced, that is, the participant needs to decide which object to choose among the available alternatives. In a target search task, spatial uncertainty is key, that is, it is unclear where the object of interest is among its distracters. Focusing on the choice process itself, van Raaij (1977) used direct observations of eye movements applying a one-way mirror and recording camera. His study revealed a pervasive use by consumers of paired comparisons between alternatives. Russo and Leclerc (1994) investigated the choice process for nondurables, building on earlier work by Russo and Rosen (1975). In a laboratory simulation of supermarket shelves, like van Raaij, Russo and Leclerc used direct observation of eye movements from video recordings through a one-way mirror. They heroically observed the complete scanpath of eye movements across the alternatives in the set, identifying three different stages in the choice process: orientation, evalua-tion, and verification, respectively. Orientation consisted of an overview of the product display. In the evaluation stage, which was the longest, direct comparisons between two or three alternative products were made. The verification stage involved further examination of the already chosen brand. Models of planned analysis of choice alternatives were disconfirmed in favor of an adaptive and constructive process. In particular, the last stage that they observed is of interest and novel, and further research may statistically test their three-state sequential model of choice. Focusing on top-down factors, Pieters and Warlop (1999) studied the impact of time pressure and task motivation on visual attention during brand choice. All brands were new, to rule out (top-down) memory effects on choice. Analysis of eye movements revealed that visual attention adapts rapidly to differences in time pressure and task motivation, two important contextual factors, underscoring the findings of Russo and Leclerc (1994). Under high time pressure, con-sumers accelerated information acquisition, as revealed by a decrease in the average duration of eye fixations. Moreover, participants filtered information by skipping textual information on the packaging. Under high time pressure, consumers also shifted to a processing-by-attribute strategy,