This project explores and analyzes coffee sales data to uncover insights about product performance, customer preferences, seasonal trends, and regional sales patterns. The goal is to help stakeholders make data-driven decisions to boost profitability and optimize inventory management. Espresso is the highest-selling product across all regions.
Sales peak during winter months (October–December).
North region accounts for 35% of total revenue.
A noticeable decline in sales during summer suggests potential for cold beverage promotions.
This project analyzes coffee shop sales data to uncover insights into product performance, customer preferences, seasonal trends, and regional sales patterns. The goal is to help stakeholders make data-driven decisions to boost profitability, improve marketing strategies, and optimize inventory management.
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Top Product:
Espresso is the highest-selling product across all regions, indicating consistent customer preference. -
Seasonal Trends:
Sales peak during the winter months (October–December), while a decline is observed during the summer. This suggests potential for promoting cold beverages in warmer seasons. -
Regional Performance:
The North region accounts for 35% of total revenue, making it the top-performing area in terms of sales.
- Python (Pandas, Matplotlib, Seaborn)
- Jupyter Notebook
- Excel/CSV for raw data
- Power BI / Tableau (optional for visualization)