Visual search strategies of product attributes on dairy product packages - A comparative study of two methods to define areas of interests (AOIs)

Abstract

Current study examines the applicability of two different approaches in evaluation of consumers’ information search processes on yogurt packages. Our main research question is whether the self-designated AOIs or the data driven cluster areas can predict better the consumers’ preferences and choice. Eighty-five students of two Hungarian universities participated in the study, where nine strawberry yogurt pictures from different brands served as stimuli. First we conducted the A01 analysis based on the main attributes of yogurt packages: flavor, brand, and ingredients. We presume that these AOIs are representing the areas consumers may scan before product choice. Then, with Tobii Studio 3.0 eye tracking analysis software we generated clusters for the same yogurt stimuli. Descriptive data suggests that the cluster algorithm is calculating bigger areas than the size of the self-designated AOIs. These AOIs, based on marketing assumptions, were too strictly drawn (concentrating only on the attributes), while the consumers’ information search seems to be fuzzier, incorporating nearby areas. The spatial resolution of human perception is not as detailed as we expected during the designation of AOIs, which can cause biases in the results. We are aiming to enhance ecological validity of the marketing application of eye tracking by suggesting the usage of data driven clusters. This approach may fit better to the fuzziness of consumers’ representations of packages, and information search processes, which forms the basis of consumers’ decision-making.