Analyzed 149,456 coffee shop transactions to evaluate product demand, sales performance, customer purchasing behavior, and location-level trends through an interactive Excel dashboard.
- Generated insights from ₹698.8K in revenue across 149,116 transactions and 214,470 units sold.
- Regular and Large sizes contributed 135.7K units, accounting for approximately 63% of total sales volume.
- Lower Manhattan emerged as the highest-performing location with 71.7K units sold, closely followed by Hell's Kitchen (71.1K) and Astoria (71.0K).
- Demand was concentrated among a limited group of products, with the top-selling item exceeding 13K units sold.
- Sales activity peaked during morning hours, indicating stronger demand during early operating periods.
- Product Performance
- Category Demand Analysis
- Store-Level Sales Comparison
- Size-Wise Purchasing Patterns
- Hourly Sales Trends
- Day and Month Performance Tracking
- Cleaned and transformed raw transactional data using Power Query.
- Created analytical dimensions including Revenue, Month, Day, Hour, and Size.
- Built data models using Pivot Tables and Power Pivot.
- Developed an interactive dashboard for multi-dimensional sales analysis.
Business Analytics • Sales Analysis • Demand Forecasting Support • KPI Reporting • Data Cleaning • Power Query • Power Pivot • Excel Dashboarding
Project by Anurag Chauhan