AI-Driven Sentiment Assessment and Automated Departmental Categorization for Customer Feedback

By allowing businesses to grasp how consumers feel about a product or service, sentiment analysis is very important to e-commerce. Companies can increase revenue by analyzing user-generated reviews to improve products and services, increase customer satisfaction, and tailor marketing strategies while also reducing negative feedback. The focus of this study is to develop a simple Python-based AI system that automatically classifies customer reviews as positive, neutral, or negative. It is also necessary to design a system that categorizes reviews based on business functions such as logistics, sales, and other departments. This section of the report outlines the benchmark measurement that evaluates the effectiveness of the models presented. The model for automatic sentiment classification achieved 94.2% accuracy, while the departments’ mapping model achieved an impressive 94% classification precision. Further, accurate models became enhanced by implementing an intuitive Python interface to increase accessibility and improve the experience of users.