This report analyzes customer sentiment patterns in product reviews using data visualization techniques. The analysis is based on a publicly available Flipkart product review dataset containing product names, customer reviews, and ratings.
Customer ratings were grouped into three sentiment categories. Ratings of 1 and 2 were classified as negative, rating 3 as neutral, and ratings of 4 and 5 as positive. The goal of this report is to understand the overall sentiment pattern, rating distribution, product-level review activity, and variation in customer satisfaction across products.
The dataset contains customer reviews and ratings for Flipkart products. The data was cleaned by renaming columns, grouping ratings into sentiment categories, and creating shorter product names for clearer visual presentation.
This visualization shows the overall distribution of customer sentiment in product reviews.
This histogram shows how product ratings are distributed across all customer reviews.
This chart highlights the products that received the highest number of customer reviews.
This visualization compares positive, neutral, and negative sentiment across the most reviewed products.
This chart compares the average rating of the most reviewed products. Using the most reviewed products avoids highlighting products with very few ratings.
This visualization shows the percentage share of each sentiment category in the dataset.
This interactive chart allows users to explore the distribution of customer sentiment dynamically.
This boxplot shows the spread and variation of ratings across the top reviewed products.
This analysis shows that customer sentiment in the selected product review dataset is mainly positive, with fewer neutral and negative reviews. The rating distribution also supports this pattern, as higher ratings appear more frequently than lower ratings. Product-level comparisons show that some products receive more review activity than others, and the average rating and boxplot views help compare satisfaction across frequently reviewed products.
Overall, the visualizations provide a clear view of customer feedback patterns and demonstrate how product review data can be used to understand customer sentiment in a practical way.