Overview
Analyzed a retail transaction dataset to decode purchasing patterns, identify high-value customer segments, and surface product performance insights using Python and Pandas.
Key Findings
- Uncovered that 30–50 year-olds drive the highest average spend per transaction.
- Identified top-performing product categories contributing to 60%+ of total revenue.
- Provided a clear segmentation target for marketing optimization to drive sustainable revenue growth.
Tools & Stack
Python · Pandas · Seaborn · Matplotlib · Tableau · EDA