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 visualisation 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 visualised and statistically assessed .