Exploring Chatbot Implementation Methodologies used in Customer Support Industry
T. Suganya1, N. S. Ashwin Kumar2, Kavijha R.3
1T. Suganya., M. E., Assistant Professor, Department of Computer Science and Engineering in Sri Krishna college of Technology, Coimbatore, Tamil Nadu, India.
2Ashwin Kumar N. S., Department of Computer science and Engineering at Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India.
3Kavijha R., Department of Computer science and Engineering at Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India.
Manuscript received on March 12, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on March 30, 2020. | PP: 3603-3607 | Volume-8 Issue-6, March 2020. | Retrieval Number: F8895038620/2020©BEIESP | DOI: 10.35940/ijrte.F8895.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In an IT industry, technical support is a huge sector which requires a lot of manpower and other resources. Although huge organizations have a dedicated group of people working on it, small companies could not afford to have a separate department for managing customer queries. Automation in industry is associated with faster production and cheaper labor costs. By leveraging today’s technologies such as Machine learning and Natural Language Processing, the process of handling user’s queries such as complaints about a certain product, feedback, customer experience, and clarifications could be automated using intelligent agents (chatbots) that are able to understand the user’s query and assist them accordingly. This process of automating user query handling using chatbots has been the main interest of multiple organizations and would result in saving a lot of resources as well as improve overall customer experience.This paper is a comprehensive exploration of how chatbots have evolved over time and what methodologies are being used to implement these chatbots across different organizations.
Keywords: Automation, Chatbot, Machine Learning, Natural Language Processing.
Scope of the Article: Machine Learning.