This project focuses on Descriptive Analytics for a Quick Commerce business model (similar to Blinkit, Zepto, and Instamart). The goal was to analyze 1,000+ delivery transactions in Gurugram to monitor operational efficiency and customer satisfaction.
- Hyper-local Tracking: Detailed performance analysis for specific zones like Sector 45, Cyber Hub, and Sohna Road.
- Operational KPIs: Monitoring of Average Delivery Time, Order Accuracy (POR%), and Revenue trends.
- Customer Sentiment Analysis: Integration of star ratings and a Word Cloud to identify common customer pain points.
- Interactive Filters: Dynamic slicers for Order Status (Delivered, Cancelled, Refunded) and Area.
- Tool: Power BI Desktop
- Data Source: Microsoft Excel (Cleaned & Structured)
- Key Skills: Data Visualization, KPI Benchmarking, Descriptive Reporting.
- Identified that Sector 45 had the highest concentration of late deliveries during evening peaks.
- Discovered a direct correlation between delivery latency and a 15% drop in average ratings.
- Download the
.pbixfile from this repository. - Open with Power BI Desktop to interact with the live dashboard.