Abstract:
This research explores how text analytics can reveal consumer concerns by examining reviews of
brands such as Khaadi, J., Ideas by Gul Ahmed, Limelight, and Sapphire on Google. The study is
divided into two main sections: the first highlights the significance of text analytics in discerning
consumer preferences, personalizing experiences, and identifying trends within the fashion sector.
The second section focuses on the methodology of data preprocessing, modeling, and the analysis
of customer feedback in the Pakistani fashion market. Using a four-step approach—data collection,
preprocessing, topic modeling, and sentiment analysis—this research aims to evaluate how these
top online retail brands are perceived based on customer reviews. Adhering to ethical standards
for data handling, the study seeks to provide actionable insights into brand performance and
customer perceptions. By leveraging multiple analytical methods, this research aims to convert
unstructured social media data into valuable insights that can enhance retail strategies and
customer engagement.
