This project focuses on analyzing e-commerce transactional data to understand customer purchasing behavior, product performance, and sales trends through data cleaning, exploratory data analysis (EDA), and dashboard visualization.
- Analyze monthly sales trends
- Identify top-performing products
- Understand customer purchasing behavior
- Visualize business KPIs through an interactive dashboard
- Python (Pandas, Matplotlib)
- Excel
- Looker Studio
- Handled inconsistent date formats
- Treated missing values using median and average imputation
- Standardized transaction data
- Revenue peaked in December 2022 and May 2023
- Tunic became the top revenue-contributing product
- Customer payment preferences remained balanced between Credit Card and Cash
- Customer ratings remained relatively stable around 3.0
-
