NLP Chatbot For Order Assistance Using Dialogflow

Abstract

This paper explains the development of an order assistant conversational AI chatbot with Dialogflow. The chatbot will be created for an improved experience, more customer interaction, and simplicity in placing orders. The current study looks into how NLP chatbots will likely revolutionize customer service operations. The existing systems designed for order assistance are generally ineffective. This increases customer frustration and reduces loyalty. Manual handling of customer queries increases response rate the operational cost and makes the very slow. An automated system with efficient order processing and the possibility of personalizing support would be great.  The approach to design an NLP chatbot using Dialogflow in a manner through which machine learning and natural language understanding could be integrated. This chatbot will target the purpose of customer queries and product information, especially in placing an order or tracking it. A user-centric approach will be used to avoid complexity during chat. From the results, it is evident that a chatbot can effectively handle customer queries with an accuracy rate of 90%. Operational costs are reduced by 30%, while response times are shortened by 50%. The level of chatbot performance that is implemented is very gratifying for users since it increases customer experience and loyalty. This research shows that NLP chatbots can revolutionize support in order assistance and customer service. The delivered chatbot solution will ensure that cost-effective and scalable improvements are brought to customer service.