The Influence of Chatbot Service Features on Purchase Intentions

Abstract

This article examines how chatbot service features shape purchase intention among chatbot users and online shoppers in Pakistan. Drawing on the DeLone and McLean information systems success model and the stimulus–organism–response framework, the study tests whether information quality, system quality, chatbot experience, and perceived customization influence purchase intention through customer satisfaction and brand relationship quality. Data were collected through an online questionnaire from 160 respondents with prior chatbot interaction experience and analyzed using partial least squares structural equation modeling (PLS-SEM) in SmartPLS. The measurement model showed acceptable reliability and validity. In the structural model, information quality (β = 0.456, p = 0.002) and chatbot experience (β = 0.273, p = 0.021) significantly increased customer satisfaction, whereas system quality (β = −0.088, p = 0.492) and perceived customization (β = 0.239, p = 0.077) were not statistically significant. Customer satisfaction significantly strengthened brand relationship quality (β = 0.477, p < 0.001), but neither customer satisfaction nor brand relationship quality had a significant direct effect on purchase intention. Indirect effects showed that customer satisfaction transmitted the effects of information quality and chatbot experience to brand relationship quality, while the sequential indirect paths to purchase intention remained non-significant. The findings suggest that brands can use chatbots to improve satisfaction and relationship outcomes, yet additional determinants are needed to convert favorable chatbot experiences into stronger purchase intention in the Pakistani e-commerce context.