Smart Customer Behaviour and Sentiment Analysis Application

The Smart Customer Behaviour and Sentiment Analysis Web Application Project uses Natural Language Processing (NLP) and Machine Learning (ML) to analyze customer reviews, ratings, and behavioural data from e-commerce platforms. The system preprocesses customer feedback, extracts important textual features using TF-IDF, and classifies reviews into positive, negative, and neutral sentiments using machine learning algorithms such as Logistic Regression, Naive Bayes, and Support Vector Machine (SVM). It also analyzes customer behaviour patterns, satisfaction levels, preferences, and purchasing trends to generate meaningful business insights. The results are presented through dashboards and visualizations that help businesses improve customer experience, personalize recommendations, and support data-driven decision-making. The proposed framework is simple, interpretable, scalable, and can be extended with advanced AI models in the future.