Smart-E-commerce-Sales-Management-System-Project

Smart E-Commerce Sales Management System A comprehensive data analysis project for an E-Commerce sales management system, designed to transform raw data into actionable strategic insights. The system was built by analyzing a complete dataset encompassing customers, products, orders, payments, and shipping.

Key Features:

Sales Performance Analysis: Track revenue, order volume, and top-selling products.

Customer Behavior Analysis: Identify the most valuable customer segments, purchasing patterns, and seasonal shopping trends.

Operational Efficiency Evaluation: Analyze shipping success rates, delivery times, and payment method performance.

Interactive Dashboard: Visualize key findings and insights through clear and effective data visualizations.

Predictive Model: Forecast future sales using machine learning techniques.

Tech Stack & Tools:

Programming Languages: Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn)

Database & Querying: SQL (Designed a full ERD and executed complex queries)

Data Visualization: Power BI / Tableau (for building interactive dashboards)

Version Control & Collaboration: GitHub

Outcomes & Deliverables:

Provided actionable recommendations to boost sales, enhance customer satisfaction, and improve operational efficiency.

Built a smart predictive model capable of forecasting sales volume for upcoming months, aiding management in strategic planning.