AI-Powered Chatbots as a Marketing Tool: Customer Perception and Trust

Abstract

Chatbots that use AI are becoming more and more popular in marketing very quickly. They help businesses talk to customers in real time, give them personalised suggestions, and make it easier to deliver services. Even though these digital agents are becoming more common, it\u27s still not clear how much customers trust them or how they feel about them. This paper examines the effectiveness of AI chatbots as a marketing instrument, concentrating on customer perception, trust, and engagement. The data were gathered using a mixed-method research design, incorporating surveys and comprehensive interviews with 350 consumers who have engaged with AI chatbots in diverse sectors, such as e-commerce, banking, and telecommunications. The quantitative analysis employed descriptive statistics and a structural equation model to clarify the interrelations among perceived usefulness, conversational quality, personalisation, and trust. Thematic analysis was utilised to extract qualitative data from interview transcripts, concentrating on customer attitudes, satisfaction, and apprehensions related to privacy and transparency. The results show that chatbots are better at marketing when their answers are correct, they are easy to use, and the conversations seem human-like. Trust is an important link between how well a chatbot works and how interested a customer is. Being open about how AI is used and how data is handled greatly increases trust. Additionally, personalized communication and context-aware interactions were found to improve customer satisfaction and loyalty intentions. The study contributes to both theory and practice by highlighting the psychological and behavioral factors that underpin customer acceptance of AI chatbots in marketing contexts. Implications for marketers include strategies for optimizing chatbot design, building trust and fostering long-term customer relationships. Future research should explore longitudinal effects of chatbot interactions and cross-cultural differences in perception and trust