Chapter 7: Analyzing the Effectiveness of AI-Powered Chatbot's: A Smart PLS Approach for Evaluating User Engagement and Satisfaction

This research paper investigates the efficacy of artificial intelligence (AI)-powered Chatbot's in enhancing user engagement and satisfaction within various contexts. As organizations increasingly deploy Chatbot's to interact with users, understanding their impact on user experience becomes imperative. The study employs Smart partial least squares (PLS) as a robust analytical tool to assess the multifaceted dimensions of AI-powered Chatbot interactions. The research focuses on user engagement, examining the Chatbot's ability to captivate users and sustain their interest throughout interactions. Additionally, user satisfaction is explored to gauge the overall effectiveness of the Chatbot in meeting user expectations. The proposed model integrates key variables, including the Chatbot's responsiveness, conversational abilities, and problem-solving capabilities, to comprehensively evaluate its impact. The methodology involves collecting data from diverse user groups to ensure a representative sample. Smart PLS, a powerful structural equation modeling technique, is employed to analyze the relationships between the identified variables. The findings are expected to contribute valuable insights into the factors influencing user engagement and satisfaction in the context of AI-powered Chatbots. The implications of this research extend beyond theoretical understanding, offering practical recommendations for organizations seeking to optimize their Chatbot implementations. By leveraging Smart PLS, this study aims to provide a nuanced understanding of the intricate dynamics involved in AI-powered Chatbot interactions, ultimately guiding the development and deployment of more effective and user-centric conversational agents.