Predicting Product Preferences on Retailers' Web Shops through Measurement of Gaze and Pupil Size Dynamics.

Abstract

Previous studies used gaze behavior to predict product preference in value-based decision-making, based on gaze angle variables such as dwell time, fixation duration and the first fixated product. While the application for online retail seems obvious, research with realistic web shop stimuli has been lacking so far. Here, we studied the decision process for 60 Dutch web shops of a variety of retailers, by measuring eye movements and pupil size during the viewing of web shop images. The outcomes of an ordinal linear regression model showed that a combination of gaze angle variables accurately predicted product choice, with the total dwell time being the most predictive gaze dynamic. Although pupillometric analysis showed a positive relationship between pupil dilation and product preference, adding pupil size to the model only slightly improved the prediction accuracy. The current study holds the potential to substantially improve retargeting mechanisms in online marketing based on consumers’ gaze information. Also, gaze-based product preference proves to be a valuable metric in pre-testing product introductions for market research and prevent product launches from failure.