Customer Review Intelligence: A Sentiment Driven Product Quality Assessment Using NLP

Author(s)	Bandari Nithin, Ailineny shiva keerthana, Teepi Vineeth Reddy, T .Venkata Subbamma
Country	India
Abstract	With the proliferation of e-commerce platforms, understanding customer sentiment from reviews has become vital for product improvement. Traditional manual methods of review analysis are inefficient and error-prone. In this paper, we propose an automated system that leverages Natural Language Processing (NLP) and Machine Learning (ML) to assess product quality based on customer feedback. Using sentiment classification and topic modeling, we extract insights from raw review data. The proposed system achieves high accuracy using logistic regression and provides data visualizations for product managers and marketing teams to make data-driven decisions.
Keywords	NLP, Sentiment Analysis, TF-IDF, Logistic Regression, Review Mining, Customer Feedback, Product Quality.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-04-23
Cite This	Customer Review Intelligence: A Sentiment Driven Product Quality Assessment Using NLP - Bandari Nithin, Ailineny shiva keerthana, Teepi Vineeth Reddy, T .Venkata Subbamma - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.4034
DOI	https://doi.org/10.71097/IJSAT.v16.i2.4034
Short DOI	https://doi.org/g9gp36

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