Chatbots are very widely used nowadays. However, much of the research on Chatbots have had a technology focus or has been limited to studies of adoption. To take advantage of the potential associated with chatbots, research that addresses the issues online users face when interacting with such programs is needed. The study described in this paper used the task-to technology fit theory to address the question of how individual characteristics and task/technology requirements influence the performance and utilization of chatbots. This paper used the quantitative methodology over two sets of data collected independently from two different populations. The first dataset of 100 respondents was obtained firstly through a structured questionnaire administered at Linnaeus University Campus in Växjö. The respondents are students in the university who use chatbots regularly. A second dataset was also collected from 20 participants through a practical test experiment with three different chatbots (Eliza, Rose, and Watson). The result and the data were then recorded through an online interview via the zoom application. The two datasets were analyzed quantitatively using comparative factor analysis with the aid of Smart PLS software. While few variables provided little support for the claims, the majority of the variables show strong support for the importance of task–technology fit, as a measure of chatbot utilization and performance based on individual characteristics as well as the task/technology requirements.