This study uses a combination of user testing and analysis to evaluate the impact of brush and tooltip on the comprehension of time series visualizations. Employing a sequential mixed-methods approach, with qualitative data from semi-structured interviews used to inform the design of a visualization tool, followed by a quantitative user study to validate it. Sixteen (16) participants from various fields of study, predominantly computer science, participated in the study. A MANOVA test was conducted with results indicating a significant statistical difference between the groups. Results deriving from the study show that the use of brush and tooltip increases user accuracy on detecting outliers, as for perception of trends and patterns. The study’s context was limited to desktop usage, and all participants were treated as a homogenous group, presenting potential limitations in applying these findings to other devices or more diverse user groups. The results provide information about improving time series data visualizations for facilitating more efficient and effective understanding, which can be relevant specifically to data analysts and academic researchers.