E-Commerce Sales Data Visualization and Forecasting System

Abstract

Quick-commerce and e-commerce platforms such as Zepto, Blinkit, Swiggy, and Zomato generate large volumes of operational and sales data. Analyzing this data is essential for demand forecasting, inventory management, and improving delivery efficiency. This project presents an E-commerce and Quick-commerce Sales Data Visualization and Forecasting System that helps businesses make data-driven decisions. The system integrates multi-source sales data and performs automated preprocessing to manage variations in product categories, delivery times, geolocation, and customer purchase behavior. Interactive dashboards display key metrics such as order volumes, revenue trends, delivery time analysis, top-selling products, customer purchase frequency, and location-based demand patterns, enabling businesses to gain insights and improve operational performance.