ENHANCING CUSTOMER EXPERIENCE AND ENGAGEMENT THROUGH AI CHATBOTS IN CRM

Abstract

In the emerging digital transformation paradigm, AI chatbots have become central components of Customer Relationship Management (CRM) systems. This research investigates how particular characteristics of AI chatbots—responsiveness, personalization, and usability—improve two primary CRM outcomes: Customer Experience (CX) and Customer Engagement (CE). According to the Technology Acceptance Model (TAM) and SERVQUAL model, the research integrates qualitative and quantitative research. Data were collected among 350 bank, telecom, and e-commerce sector CRM users, and 15 CRM experts. With Structural Equation Modeling (SEM) using AMOS and thematic coding using NVivo, the study determines that chatbot responsiveness and ease of use have a great influence on customer experience, while personalization influences customer engagement and interaction. Trust emerged as a partial mediator between engagement and experience and necessitates openness in engaging with AI. Between the platforms in consideration—GPT-4, Dialogflow, and Watson Assistant—GPT-4 possessed superior linguistic proficiency, and Dialogflow and Watson enjoyed platform integration advantages. The findings emphasize the strategic importance of creating AI chatbots that not only function effectively but also work emotionally and are accessible.