This project has been developed with the target of aiding Etsy sellers in making informed decisions about their business endeavors. It involves the utilization of web scraping techniques to gather pertinent data from the Etsy platform. Through analysis and interpretation of this data, sellers can gain insights into their performance and customer feedback, enabling them to assess whether to continue selling on Etsy or explore alternative avenues.

EXPLORE DETAILED DOCUMENTATION AND THE FULL PROJECT ON GITHUB—CLICK THE LINK TO VIEW

The application verifies the suitability of the provided data by ensuring it contains essential columns such as reviews, item ratings, and shipping ratings.

Once confirmed, the app proceeds to preprocess the data, correcting any errors and preparing it for analysis. Subsequently, the application employs sentiment analysis techniques to gauge the sentiment expressed in customer reviews, determining whether they are positive, negative, or neutral.

Finally, leveraging the processed data and sentiment analysis results, the app calculates the overall Customer Satisfaction Index (CSI) value, providing insights into customers' satisfaction levels with the products or services. Through these four key components, the Flask app facilitates comprehensive data handling and analysis, empowering users to gain valuable insights into customer sentiments and satisfaction.

The readme file in github contains a clear explanation on how the CSI value is calculated

After submission: