The Role of Chatbots in Customer Service: Examining Language Use and Its Impact on Customer Satisfaction
Keywords:
Communication Styles, Chatbots, Customer Satisfaction, Mind Perception Theory, Cross-Cultural Comparisons.Abstract
In the digital age, chatbots have become a pivotal tool in customer service, offering businesses the ability to provide 24/7 support and enhance customer interactions. This article explores the impact of chatbot communication styles on customer satisfaction, trust, and engagement, particularly in the context of service failures. Drawing on recent research, we examine how task-oriented and social-oriented communication styles influence consumer perceptions and behaviors. We also investigate the role of expectancy violations and mind perception theory in shaping these interactions. Our findings suggest that social-oriented chatbots, which exhibit empathy and warmth, significantly enhance customer satisfaction and trust, especially in high-expectancy violation scenarios. This study provides valuable insights for businesses aiming to optimize chatbot interactions and improve customer service experiences.
References
Adam, M., Wessel, M. and Benlian, A. (2020) 'AI-based chatbots in customer service and their effects on user compliance', Electronic Markets, 31(2), pp. 427–445.
Belanche, D., Casaló, L.V. and Flavián, C. (2020) 'Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success', Journal of Service Management, 31(2), pp. 267–289.
Crolic, C., Thomaz, F., Hadi, R. and Stephen, A.T. (2022) 'Blame the bot: Anthropomorphism and anger in customer-chatbot interactions', Journal of Marketing, 86(1), pp. 132–148.
Roy, R. and Naidoo, V. (2021) 'Enhancing chatbot effectiveness: The role of anthropomorphic conversation styles and time orientation', Journal of Business Research, 126, pp. 23–34.
Tsai, W.H.S., Liu, Y. and Chuan, C.H. (2021) 'How chatbots’ social presence communication enhances consumer engagement: The mediating role of parasocial interaction and dialogue', Journal of Research in Interactive Marketing, 15(3), pp. 460–482.
Kim, J. and Sundar, S.S. (2023) 'Cultural differences in chatbot interactions: The role of collectivism and individualism in shaping user trust', Computers in Human Behavior, 145, pp. 1–14.
Liu, X., Zhang, L. and Chen, M. (2022) 'Emotional AI in chatbots: How sentiment analysis improves customer satisfaction during service recovery', International Journal of Human-Computer Studies, 168, pp. 102–115.
Patel, R. and Lee, H. (2021) 'Longitudinal effects of chatbot interactions on customer loyalty: A three-wave study', Journal of Retailing and Consumer Services, 63, pp. 102–112.
Müller, L., Tanaka, K. and Al-Mutawa, N. (2020) 'Cross-cultural preferences for chatbot communication styles: A comparative study of Germany, Japan, and Saudi Arabia', Cross Cultural & Strategic Management, 27(4), pp. 589–607.
Zhang, Y. and Wang, Q. (2023) 'Advanced natural language processing in chatbots: The impact of contextual understanding on customer satisfaction', Artificial Intelligence Review, 56(3), pp. 201–220.
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Copyright (c) 2025 Nargis Parveen, S Noor Afshan, Priyanka Srivastava, Rula Y Hajjaj, Hadia A. Osman, Nada A. Adam, Nouf Mutlaq S Alotaibi, Shama Mashhour M Alqahtani

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