Statistical Analysis of Online Eye and Face-Tracking Applications in Marketing

In the dissertation, we apply these two technologies to investigate effective online contents that are designed to attract and direct attention and engage viewers emotional responses. In the first part of the dissertation, we conduct a series of experiments that use eye-tracking technology to explore how online models' facial cues affect users' attention on static e-commerce websites.

The joint effects of two facial cues, gaze direction and facial expression on attention, are estimated by Bayesian ANOVA, allowing various distributional assumptions. We also consider the similarities and differences in the effects of facial cues among American and Chinese consumers. This study offers insights on how to attract and retain customers' attentions for advertisers that use static advertisement on various websites or ad networks.