Exploring Chatbot Anthropomorphism as a Driver of User Satisfaction and Purchase Intention Through Perceived Enjoyment and Responsiveness

This research aims to investigate the role of chatbot anthropomorphism in enhancing user satisfaction and purchase intention, with enjoyment, social presence, and responsiveness serving as mediating factors. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was adopted to evaluate 11 hypotheses by analyzing data from 390 customers of a local cellular operator using a chatbot for cellular data purchases over 6 months. The results show that anthropomorphism indirectly influences user satisfaction and purchase intent by improving a strong social presence and evoking enjoyment through relatable, human-like traits, such as empathy and conversational tone. Furthermore, responsiveness plays a critical dual role, where prompt and accurate replies fulfill functional needs for speed and satisfy psychological desires for user acknowledgment, enhancing overall communication effectiveness. Highly satisfied users exhibit a greater likelihood of following purchase recommendations, positioning chatbots as highly effective agents within the sales funnel. To optimize functionality and drive consumer conversions, developers must adopt a holistic design method that prioritizes anthropomorphic features, rapid responsiveness, and perceived enjoyment, ensuring a meaningful and satisfying user experience. These insights supported effective strategies in optimizing chatbot functionality and improving user experiences.