Clustered Insights : Improving Eye Tracking Data Analysis using Scan Statistics

Analysis of eye-tracking data in marketing research has traditionally relied upon regions of interest (ROIs) methodology or the use of heatmaps. Clear disadvantages exist for both methods. Addressing this gap, the current research applies spatiotemporal scan statistics to the analysis and visualization of eye tracking data. Results of a sample experiment using anthropomorphic car faces demonstrate several advantages provided by the new method. In contrast to traditional approaches, scan statistics provide a means to scan eye tracking data automatically in space and time with differing gaze clusters, with results able to be comprehensively visualized and statistically assessed.