Project Report: US E-commerce Strategic Sales Analysis (100K Records)
1. Executive Summary
This report details the strategic analysis of a massive dataset containing 100,000 sales records from 2020 to 2026. The project identifies key revenue drivers, optimizes shipping costs, and detects high-risk customer churn zones across major US cities using Python (Jupyter Notebook), Power BI, and Tableau.
2. Problem Statement
The client faced significant challenges in managing and interpreting large-scale transactional data:
Data Overload: Difficulty in processing 100,000+ rows to find actionable insights.
Geographical Blind Spots: Inability to identify which US cities were performing well and which were losing customers.
Profit Leakage: Lack of clarity on how shipping costs impacted the overall gross margin.
Future Uncertainty: No clear vision of sales trends moving into 2026.
3. The Solution & Methodology
Phase 1: Advanced Data Engineering (Python)
Tool: Jupyter Notebook.
Action: I performed deep-dive analysis using the Pandas library to calculate complex KPIs.
Results: * Total Sales: $1,769,272,868.61.
Best Selling Product: Gaming Chair.
Least Selling Product: Coffee Maker.
Shipping Impact: Identified that shipping costs account for only 0.44% of total sales, ensuring high profitability.
Phase 2: High-Performance Visualization (Power BI & Tableau)
Power BI Dashboard: Created an interactive dashboard featuring Donut Charts for Category performance and Ribbon Charts for City-wise sales trends.
Tableau Analytics: Built a multi-sheet dashboard providing a breakdown of product quantities and yearly revenue fluctuations.
4. Key Strategic Insights
A. Top 3 Revenue Generating Cities
Dallas: $180,606,424.00.
San Diego: $180,222,094.00.
Chicago: $179,275,856.00.
B. Category Performance
The Technology category leads the market with $446.8 Million in sales, followed closely by Home Appliances and Fitness.
C. Critical Discovery: Customer Churn Risk
Through my churn analysis, I discovered a massive decline in sales in specific cities during 2026 compared to 2025:
New York: Sales dropped by -98.36%.
Philadelphia: Sales dropped by -98.28%.
Chicago: Sales dropped by -98.28%.
Recommendation: The client must initiate immediate re-engagement campaigns in these three cities to recover lost market share.
5. Final Deliverables
Cleaned CSV Dataset: 100,000 optimized records.
Interactive Dashboards: Professional files for Power BI and Tableau.
Python Script: Complete Jupyter Notebook (.ipynb) for future automated analysis.
Summary Report: Strategic recommendations for 2026 business growth.
