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

Author(s)	T .Venkata Subbamma, Bandari Nithin, Ailineny Shiva Keerthana, Teepi Vineeth Reddy
Country	India
Abstract	With the proliferation of e-commerce platforms,understanding customer sentiment from reviews hasbecome vital for product improvement. Traditional manualmethods of review analysis are inefficient and error-prone.In this paper, we propose an automated system thatleverages Natural Language Processing (NLP) andMachine Learning (ML) to assess product quality based oncustomer feedback.Using sentiment classification and topic modeling,we extract insights from raw review data. The proposedsystem achieves high accuracy using logistic regression andprovides data visualizations for product managers andmarketing 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	2025-06-02
DOI	https://doi.org/10.71097/IJSAT.v16.i2.3946
Short DOI	https://doi.org/g9m29k

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International Journal on Science and Technology