AI in E-Commerce: Transforming Customer Interactions with NLP and Reinforcement Learning

E-commerce challenges solved by Conversational AI. E-commerce systems are restricted by the limited capabilities of traditional rule-based chatbots, which frequently fail to have complicated and contextual discussions, irritating customers and lowering consumer satisfaction. The basis of the proposed system is Natural Language Processing (NLP) like technologies, such as the usage of GPT-3-based dynamic response generation to enable contextual and tailored responses and BART for intent/acts identification models. To solve the problem more quickly and effectively, it uses techniques like sentiment analysis and reinforcement learning (RL). With an intent identification accuracy of 92% and a customer satisfaction rating of 90%, the trial results show that the proposed system performs far better than the cutting-edge, whereas existing traditional systems only manage 84% and 70%, respectively. With a response time reduced to 20 seconds, it also demonstrates more effective operation. The study’s conclusions suggest that NLP-powered systems may enhance customer experience, engagement, and retention in online sales.