Development of a Manychat Based Chatbot for Automated Customer Support System
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Abstract: In today’s fast-paced digital age, customer service demands have evolved with customers expecting prompt and accurate responses to their inquiries and request. However, traditional customer service methods often struggle to meet these expectations. The rise of artificial intelligence and natural language processing technologies present an opportunity to address these challenges through the development of intelligent chatbot system. This research aimed to develop and train a chatbot system using ManyChat that can promptly, accurately, and effectively address basic customer inquiries and handle simple request.
The methodology employed in this research involved a multi stage approach. Firstly, requirement analysis was conducted through stakeholder meetings, user feedback, and scope definition. Next, the design phase utilized user flow mapping to visualize the customer journey from the initial interaction to issue resolution. The chatbot was then developed on ManyChat platform. Following development, testing, and refinement were performed based on feedback. The performance of the chatbot was evaluated after receiving feedback from multiple users using user satisfaction, task completion rate, and ability to resolve customer inquiries.
The results of the evaluation reveal that the developed chatbot has a value of 92%, 87%, and 92% for user satisfaction, task completion rate, and ability to resolve customer inquiries respectively.
The findings underscore the ManyChat based chatbot efficiency as a reliable means of providing prompt and accurate responses to customer inquiries. This research proves how ManyChat can be used to build intelligent and scalable chatbot that can be tailored to specific business requirement, and thereby improving the customer experience.
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References
Jones and Taylor, E., L. (2023). An overview of chatbot technology. Artificial https://doi.org/10.1016/j.chb.2018.03.051 DOI: https://doi.org/10.1016/j.chb.2018.03.051
Miller and Roberts, J. (2022). Enhancing customer service using AI-driven chatbots. International Journal of Computer Applications, 177(29), 32-39.
Baykal, N., & Sagiroglu, S. (2018). Integration of AI into CRM systems. Journal of Intelligent Systems, 27(4), 553-568.
Evans, (2023). A valued agent: How ECAs affect website customers. Journal of Retailing and Consumer Services, 22, 53-62. https://doi.org/10.1016/j.jretconser.2014.09.001 DOI: https://doi.org/10.1016/j.jretconser.2014.09.001
Smith and Wang (2022). Designing for conversation: Principles of chatbot interaction design. Nielsen Norman Group. Retrieved from https://www.nngroup.com
Lee and Zhang (2021). Chatbots and customer support: A comparative study of chatbot interfaces. Information Systems Frontiers, 1-12. https://doi.org/10.1007/s10796-020-10086-y
Calderón, R., & González-Crespo, R. (2019). Customer service chatbots: Current practices and future trends. Expert Systems with Applications, 123, 215-230. https://doi.org/10.1016/j.eswa.2019.01.013 DOI: https://doi.org/10.1016/j.eswa.2019.01.013
Chaves, A. P., & Gerosa, M. A. (2021). How should my chatbot interact? A survey on social characteristics in human-chatbot interaction design. International Journal of Human Computer Interaction, 37(8), 729-758. https://doi.org/10.1080/10447318.2020.1841438 DOI: https://doi.org/10.1080/10447318.2020.1841438
Cho, Y. H., & Park, J. S. (2021). Chatbot interaction styles and their impact on customer service satisfaction. Journal of Service Management, 32(5), 815-830.
Dahiya, M. (2017). A tool of conversation: Chatbot. International Journal of Computer Sciences and Engineering, 5(5), 158-161.
Diederich, S., Brendel, A. B., & Kolbe, L. M. (2019). Designing anthropomorphic enterprise chatbots. International Conference on Information Systems (ICIS).https://aisel.aisnet.org/icis2019/digitalinnovation/digital_innovation/9/
Dutta, S., & Bose, S. (2020). The impact of chatbots on customer service: A comparative analysis. Journal of Business Research, 112, 84-95.
Følstad, A., & Brandtzaeg, P. B. (2020). Users’ experiences with chatbots: Findings from a questionnaire study. Quality and User Experience, 5(1), 1-14. https://doi.org/10.1007/s41233-019-00206-1 DOI: https://doi.org/10.1007/s41233-020-00033-2
Følstad, A., Nordheim, C. B., & Bjørkli, C. A. (2018). What makes users trust a chatbot for customer service? An exploratory interview study. Proceedings of the 16th IFIP TC.13 International Conference on Human-Computer Interaction, 194-208. https://doi.org/10.1007/978-3-319-91664-915 DOI: https://doi.org/10.1007/978-3-030-01437-7_16
Gnewuch, U. Morana, S., & Maedche, A. (2017). Towards designing cooperative and social conversational agents for customer service. Proceedings of the International Conference on Information Systems (ICIS). https://aisel.aisnet.org/icis2017/HCI/Presentations/10/
Griol, D. Molina, J. M., & De Miguel, A. S. (2013). A statistical approach to develop multi domain spoken dialogue systems in mobile environments. Neurocomputing, 113, 25 36.
Hadjikhani, A., & Thilenius, P. (2020). AI and customer service: Strategic implications of AI chatbots in B2B settings. Industrial Marketing Management, 89, 475-484.
Haddad, P., Singh, M., & Xue, Y. (2020). Integrating CRM systems with conversational agents: A survey of the landscape and research directions. Journal of Systems and Software, 162, 110513. https://doi.org/10.1016/j.jss.2019.110513
Hill, J., Randolph Ford, W., & Farreras, I. G. (2015). Real conversations with artificial intelligence: A comparison between human–human online conversations and human chatbot conversations. Computers in Human Behavior, 49, 245-250. https://doi.org/10.1016/j.chb.2015.02.026 DOI: https://doi.org/10.1016/j.chb.2015.02.026
Hu, T., & Caverlee, J. (2019). Understanding the dynamics of chatbot development: A large scale analysis. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1-25.
Jaf, S., & Dokoohaki, N. (2019). The role of artificial intelligence in enhancing customer relationship management. Information Systems Frontiers, 21(5), 1027-1040.
Jain, M., Kumar, P., & Scott, S. D. (2018). Evaluating and informing the design of chatbots.Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 112. https://doi.org/10.1145/3173574.3174138 DOI: https://doi.org/10.1145/3196709.3196735
Ji, Y. G., & Tsui, E. (2018). Enhancing knowledge management with chatbots: Case studies and best practices. Journal of Knowledge Management, 22(3), 517-528.
Khanna, S., & Joshi, H. (2020). Chatbot-based customer support: A comparative study of different chatbot frameworks. Journal of Retailing and Consumer Services, 57, 102238.
Kowatsch, T., & Maass, W. (2018). The role of chatbots in digital service encounters: Evidence from a systematic review. Journal of Service Management, 29(5), 656-683.
Kull, S. (2017). The future of customer service chatbots. Service Management Group. Retrieved from https://www.smg.com
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