With third-party cookies being banned, alternative methods to assess users’ interests online are necessary. We propose that analyzing mouse cursor movements can help address this need. Based on the response activation model, we hypothesize that interest in a product will decrease the user’s movement speed and increase the number of submovements. We conducted an online study that monitored users’ mouse movements while they were presented with several products and navigated to a button to indicate purchase intention (yes/no). Following this, participants ranked their interest in each product. Contrary to our prediction, we found that product interest increased speed and decreased the submovement count. This suggests that current theories and metrics for mouse cursor tracking are insufficient for predicting product interest. Further research is needed to develop reliable measures for gauging user interest in products.
Coors, Christopher; Jenkins, Jeff; Valacich, Joseph; and Weinmann, Markus, "Understanding Product Interest through Mouse-Cursor Tracking Analysis" (2024). SIGHCI 2023 Proceedings. 7.