E-Commerce Performance & Return Analytics

An interactive dashboard focused on understanding e-commerce sales performance and product return patterns.

E-Commerce Return & Refund Analysis Dashboard My Power BI project focused on analyzing e-commerce return metrics to help reduce revenue leakage and improve customer satisfaction. ​Understanding why products are returned is key to optimizing supply chain operations and product quality. This dashboard provides a consolidated view of return trends, categories, and key drivers. ​Key Dashboard Metrics: ​Total Orders Analyzed: 97 ​Returned Units: 27 ​Return Rate: 0.20% ​Total Refund Amount: $141.22K ​Key Features & Insights: ​Monthly Trend Chart: Tracks return volume against refund amounts to identify seasonal peaks. ​Sales Channel Breakdown: Analyzes return distributions across Marketplace, Mobile App, and Website channels. ​Category Breakdown: Highlights high-volume return categories like Electronics and Fashion. ​Return Reason Matrix: Maps subcategories against primary return drivers (e.g., Damaged Product, Late Delivery, Defective Product, Not As Expected) to pinpoint root causes. ​Product-Level Detail Table: Evaluates individual item performance and return rates for targeted inventory decisions. ​Tools Used: Power BI | Data Modeling | Data Visualization | DAX