This paper presents the results of an empirical exploration of 10 cursor movement metrics designed to measure respondent hesitation in online surveys. As a use case, this work considers an online survey aimed at exploring how people gauge the electricity consumption of domestic appliances. The cursor metrics were derived computationally from the mouse trajectories when rating the consumption of each appliance and analyzed using Multidimensional Scaling, Jenks Natural Breaks, and the Jaccard Similarity Index techniques. The results show that despite the fact that the metrics measure different aspects of the mouse trajectories, there is an agreement with respect to the appliances that generated higher levels of hesitation. The paper concludes with an outline of future work that should be carried out in order to further understand how cursor trajectories can be used to measure respondent hesitation.