An Improved Conversational Chatbot Marketing System Case on FedEx
This paper presents an innovative approach to enhancing conversational chatbot marketing systems. In a digital world, customer engagement and service personalization are paramount, and chatbots play a crucial role in this transformation. Fast forwarding to today's digital fast-paced landscape, enhancing customer interaction and service efficiency using chatbots is paramount for global logistics and courier delivery servicing companies like Federal Express FedEx. This study presents the development and integration of an improved conversational chatbot marketing system using the Rasa architecture framework. The aim of this research is to improve an existing chat bot conversational marketing system (case-on FedEx). The system will be able to give in response more accurately with respect to the user input on the messaging platform. With the vital objectives of integrating the system using RASA a machine learning framework for building conversational AI based Chatbot system. The system should be able to provide links to website home page, FAQs page and logs that the admin can see questions not answer and admin will provide the answer respectively, covering many marketing related areas. Rasa framework was chosen for its robust capabilities in building context-aware and intelligent chatbots.. The results indicate a significant reduction in response times, increased customer satisfaction, and higher engagement rates. The chatbot's ability to handle repetitive tasks and common queries allowed human agents to focus on more complex issues, thereby improving overall efficiency. This case study demonstrates the potential of advanced conversational AI systems in revolutionizing customer service and marketing strategies in the logistics industry, setting a new benchmark for digital transformation initiatives. The future work of this research will focus on further refining the chatbot's capabilities, expanding its scope to include predictive analytics, and exploring its application in other operational areas within FedEx.
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