Published Paper Details:

The rapid growth of e-commerce platforms has made online product reviews one of the most influential factors in customer purchase decisions. Consumers increasingly rely on product ratings, written reviews, and verified purchase indicators before selecting items from online marketplaces. However, the large volume of customer-generated feedback makes manual analysis inefficient and often impractical. This paper presents an internship-based analytical study titled "Online Product Review Analysis Using Power BI," which focuses on transforming raw product and customer review data into actionable business insights through interactive dashboarding and review-oriented analytics. The project integrates structured product attributes such as product category, price, discount percentage, rating, review count, brand, city, age group, delivery days, order status, and verified review status. Power BI was used as the primary business intelligence tool for data import, transformation, modeling, DAX-based KPI generation, and dashboard creation. The analytical framework supports category-wise product analysis, rating distribution, customer segmentation, verified review evaluation, and delivery-performance impact assessment. The internship dataset indicates approximately 3892 total reviews, an average rating of 3.24, and nearly 85% verified reviews, suggesting a moderately positive and comparatively reliable review environment. Results show that customer satisfaction is influenced not only by product quality and ratings but also by pricing strategy, discounts, delivery timelines, and category-specific expectations. The study demonstrates that even without complex machine learning pipelines, a well-designed Power BI dashboard can provide practical sentiment- oriented insights and decision support for e-commerce businesses. This paper highlights the importance of combining descriptive analytics with review intelligence to improve customer understanding, product strategy, and operational performance in digital marketplaces.