Data analysis project using Python, Pandas, and Matplotlib to explore customer behavior, sales performance, and business insights from an e-commerce dataset.
Analyze customer behavior and business performance using an e-commerce dataset. The goal is to understand purchasing patterns, product performance, and factors affecting sales and profit.
E-commerce dataset containing over 50,000 transactions including:
- Product categories
- Sales and profit
- Payment methods
- Customer device usage
- Discounts and shipping cost
- Python
- Pandas
- Matplotlib
- Jupyter Notebook
- Fashion category has the highest number of sales.
- Web users purchase more frequently than mobile users.
- Credit card is the most commonly used payment method.
- Sales and profit vary significantly across product categories.
- Most customers purchase small quantities of items.
- Improve mobile shopping experience to increase mobile sales.
- Focus marketing efforts on high-performing categories such as Fashion.
- Optimize discount strategy to balance sales growth and profitability.
- Enhance payment experience for credit card users.