This Power BI Dashboard provides a complete analytical view of a Coffee Shop’s performance across multiple dimensions — including Sales, Product Categories, Customer Spending Behavior, and Time-Based Trends.
The goal of this report is to help the management team make data-driven decisions by tracking key KPIs such as Total Sales, Cups Sold, Peak Hours, Weekend vs Weekday Performance, and Average Spend per Customer.
- Analyze daily, weekly, and monthly sales trends for better forecasting.
- Identify top-selling coffee types and peak hours for maximum profit.
- Compare Weekday vs Weekend spending to plan promotions effectively.
- Evaluate average spending per customer and cups sold per day.
- Provide insights into sales performance over time for business growth.
- Espresso and Cappuccino are the top-selling coffee types across all locations.
- Weekend sales show a significant 25–30% increase compared to weekdays.
- Morning hours (8 AM – 11 AM) see the highest sales volume and spending.
- Customers prefer Card and UPI payments, indicating a digital shift.
- Steady growth in total revenue observed month-over-month.
| Aspect | Details |
|---|---|
| Tools Used | Power BI, Microsoft Excel |
| Data Source | Coffee_data.csv (included in repository) |
| File Name | Coffee Trend and Spend Analysis Dashboard.pbix |
| Visual Types | Pie Chart, Column Chart, Line Chart, KPI Cards, Donut Chart |
| Purpose | To analyze coffee shop performance and support data-driven business decisions |
- Data Cleaning & Transformation using Power Query
- Data Modeling & Relationships between sales, product, and time tables
- DAX Measures for KPIs (Sales, Cups Sold, Average Spend)
- Dynamic Visuals for real-time insights and interactive exploration
- KPI Dashboard Design for management-level visibility
- Business Intelligence Storytelling for retail analytics
- ☕ Total Sales & Total Cups Sold
- 💳 Payment Mode Distribution
- 📅 Weekday vs Weekend Revenue
- ⏰ Peak Hour Analysis
- 📈 Spending Trends Over Time
- 💼 Top Performing Coffee Types
This dashboard empowers coffee shop owners and analysts to:
- Identify best-selling products and optimize the menu accordingly.
- Determine busy hours and staffing needs efficiently.
- Increase revenue with targeted promotions and offers during low-sale periods.
- Improve inventory and resource planning based on data trends.
- Enhance customer experience with insights on spending patterns.
Dataset: Coffee Shop Sales Data (CSV format)
Created for learning and portfolio purposes to demonstrate real-world business analytics in Power BI.
License: Open Educational Use (Creative Commons Attribution)
**Created by:Paramesh Mandapaka 📧 mandapakaparamesh9@gmail.com
⭐ If you find this project helpful, give it a star on GitHub!