A Study on Customer Perception towards Chatbot-unable CustomerServices: An Empirical Study of Service Effectiveness andSatisfaction

Authors

  • Sudeep Jain
  • VASANTHI REENA WILLIAMS
Published 2026-09-08
Section Research Paper
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Keywords:

Chatbots Customer Perception Customer Satisfaction Artificial Intelligence Customer Service Service Quality Technology Acceptance Model

Abstract

Chatbots have become an integral part of digital customer service strategies across banking, e-commerce, telecommunications, and hospitality. While organizations increasingly adopt AI-based conversational agents to reduce cost and improve responsiveness, the ultimate success of such systems depends on how customers perceive and accept them. This study examines customer perception towards chatbot-based customer services, with specific objectives of analyzing customer satisfaction, evaluating the effectiveness of chatbots in improving customer experience, and examining the level of query redressal achieved through chatbot interactions. A descriptive research design was adopted, and primary data were collected from 400 respondents who had prior experience using chatbot-based customer support, using a structured, Likert-scale questionnaire distributed through Google Forms, social media, and email. Convenience sampling was used to select respondents. Data were analyzed using percentage analysis, Chi-square tests, one-sample t-tests, and linear regression. Results show that respondents are predominantly young (21–30 years), educated, and moderately to highly satisfied with chatbot services, particularly regarding response speed and 24/7 availability. Chi-square tests confirmed statistically significant associations between customer responses and all measured service dimensions (p < 0.05). One-sample t-tests revealed that all effectiveness indicators exceeded the neutral midpoint, with availability recorded as the strongest attribute (mean = 4.02). Regression analysis showed that the proposed predictors explained 70.9% of the variance in overall chatbot effectiveness, with issue-resolution speed as the strongest predictor. The study concludes that chatbot services meaningfully enhance customer experience but perform best when combined with a pathway to human support for complex queries, and offers practical suggestions for improving chatbot accuracy, usability, and emotional responsiveness.

References

  1. Adamopoulou, E., & Moussiades, L. (2020). Chatbots: History, technology and applications. Machine Learning with Applications, 2, 100006. https://doi.org/10.1016/j.mlwa.2020.100006
  2. Xu, Y., Zhang, J., & Deng, G. (2022). Enhancing customer satisfaction with chatbots: The influence of communication styles and consumer attachment anxiety. Frontiers in Psychology, 13, 902782. https://doi.org/10.3389/fpsyg.2022.902782
  3. Xu, Y., et al. (2022). The effects of chatbot service recovery on customer satisfaction. Frontiers in Psychology, 13, 922503. https://doi.org/10.3389/fpsyg.2022.922503
  4. Murwati, E., & Aldianto, L. (2022). Exploring voice of customers to chatbot for customer service with sentiment analysis. ASEAN Journal of Technology Management, 15(2). https://doi.org/10.12695/ajtm.2022.15.2.4
  5. Shendge, R. (2022). Chatbots and customer service satisfaction. Journal of Contemporary Issues in Business and Government, 28(4).
  6. Zhou, L. (2023). Chatbot improves customer service in four important industries. In Proceedings of the 2023 International Conference on Computer, Machine Learning and Artificial Intelligence (CMLAI), 39. https://doi.org/10.54097/hset.v39i.6551
  7. Han, S., Yang, H., & Kim, J. (2023). Understanding user satisfaction and loyalty of customer service chatbots. Journal of Retailing and Consumer Services. https://doi.org/10.1016/j.jretconser.2022.103211
  8. Aydın, G., & Taşçı, D. (2020). Determinants of customer satisfaction in chatbot use. International Journal of Bank Marketing, 44(3). https://doi.org/10.1108/IJBM-02-2020-0056
  9. Hill, J., Ford, W. R., & Farreras, I. G. (2015). Real conversations with artificial intelligence. Computers in Human Behavior, 49, 245–250. https://doi.org/10.1016/j.chb.2015.02.026
  10. McLean, G., & Osei-Frimpong, K. (2019). Chatbots and customer engagement. Computers in Human Behavior, 98, 294–301. https://doi.org/10.1016/j.chb.2019.04.018
  11. Huang, M.-H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2). https://doi.org/10.1177/1094670517752459
  12. Dwivedi, Y. K., et al. (2021). Artificial intelligence in marketing. Journal of Business Research, 125, 520–532. https://doi.org/10.1016/j.jbusres.2020.12.020 [13] Chi, O. H., Gursoy, D., & Chi, C. G. (2021). Artificial intelligence devices in tourism service. Journal of Travel Research, 60(8), 1543–1559. https://doi.org/10.1177/0047287520952017
  13. Prentice, C., et al. (2022). Intelligent voice assistants and brand attachment. Journal of Revenue and Pricing Management, 21(2), 147–152. https://doi.org/10.1057/s41262-022-00274-y
  14. Balakrishnan, J., & Dwivedi, Y. K. (2022). Conversational commerce and digital assistants. Annals of Operations Research, 316(1), 1–4. https://doi.org/10.1007/s10479-022-04895-y
  15. Park, K., Cha, M., & Rhim, E. (2018). Positivity bias in customer satisfaction ratings. arXiv preprint. https://arxiv.org/abs/1803.03346
  16. Park, K., et al. (2015). Mining the minds of customers from online chat logs. arXiv preprint. https://arxiv.org/abs/1510.01801
  17. Isa, N. A. N. M., Jawaddi, S. N. A., & Ismail, A. (2024). Evaluation of machine learning models for customer service chatbots. arXiv preprint. https://arxiv.org/abs/2409.18568
  18. Brun, A., Liu, R., Shukla, A., Watson, F., & Gratch, J. (2025). Emotion-sensitive conversational AI. arXiv preprint. https://arxiv.org/abs/2502.08920 [20] Kotler, P., & Keller, K. L. (2016). Marketing management (15th ed.). Pearson Education.
  19. Kothari, C. R., & Garg, G. (2019). Research methodology: Methods and techniques (4th ed.). New Age International Publishers.

Published

2026-09-08

How to Cite

A Study on Customer Perception towards Chatbot-unable CustomerServices: An Empirical Study of Service Effectiveness andSatisfaction. (2026). NOLEGEIN-Journal of Global Marketing, 9(2). https://mbajournals.in/index.php/JoGM/article/view/2050

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