Paper Title
Handling E-Commerce Customer Reviews Using NLP-Enabled AI Virtual Assistant

Abstract
Customer reviews are integral to the e-commerce ecosystem, serving as a crucial factor influencing customer purchase decisions. These reviews provide prospective buyers with insights into the quality and reliability of goods and services, directly impacting sales and business reputation. This research presents the development of an NLP-Enabled AI virtual assistant aimed at enhancing the management of customer reviews on e-commerce platforms through advanced sentiment analysis. The assistant automates the detection and handling of negative customer reviews, thereby improving response times and operational efficiency for e-commerce businesses. By harnessing the power of Natural Language Processing (NLP) and Machine Learning, coupled with the advanced capabilities of the Google Cloud Natural Language API, the system efficiently identifies negative sentiments and promptly alerts sellers to potentially harmful reviews, enabling proactive and responsive customer service. The results demonstrate the virtual assistant’s capability to manage real-time customer reviews with high accuracy and speed, significantly reducing the workload on human moderators and improving customer satisfaction and business enhancement. The system’s design also considers ethical implications, ensuring fairness, privacy, and security in handling sensitive customer data. Future work will focus on expanding the system’s multilingual capabilities, enhancing integration with various digital platforms, and incorporating more sophisticated AI algorithms to predict customer behaviours and preferences. This research illustrates the potential of an AI-driven tool to transform customer relationship management in e-commerce, paving the way for more responsive and intelligent platforms. Keywords - AI-based Virtual Assistant, E-commerce, Customer Reviews, Sentiment Analysis, Review Moderation.