Customer Behavior Analysis is an end-to-end data analytics project that analyzes customer purchasing patterns, demographics, subscription behavior, and sales trends. Using Python, SQL, and Power BI, the project transforms raw customer data into interactive dashboards and actionable business insights.
A retail company wants to understand customer shopping behavior to improve sales, customer retention, and marketing strategies through data-driven decision-making.
This project follows a complete end-to-end analytics pipeline:
- 📄 Define the Business Problem
- 🐍 Perform Data Cleaning & EDA using Python
- 🗄️ Analyze Business Questions using SQL
- 📊 Build Interactive Dashboard in Power BI
- 📝 Generate Business Report
- 🎤 Present Insights using Gamma AI
- 📂 Publish Project on GitHub
| Technology | Purpose |
|---|---|
| 🐍 Python | Data Cleaning & EDA |
| 🗄 SQL | Business Analysis |
| 📊 Power BI | Dashboard & Visualization |
| 🐼 Pandas | Data Manipulation |
| 🔢 NumPy | Numerical Operations |
| 💻 Git & GitHub | Version Control |
- 👥 Customer Analysis
- 💰 Revenue Analysis
- 📦 Category-wise Sales
- ⭐ Customer Rating Analysis
- 👤 Age Group Analysis
- 🎯 Subscription Analysis
- 📈 Interactive Filters
- 📦 Clothing generated the highest revenue.
- 💵 Average purchase amount is $59.76.
- ⭐ Average customer rating is 3.75.
- 👥 Most customers are non-subscribers.
- 🎯 Young Adults contribute the highest revenue.
- 🔥 Loyal customers form the largest customer segment.
Customer-Behavior-Analysis
│
├── Images
│ ├── banner.png
│ ├── dashboard.png
│ └── project_workflow.jpg
│
├── Business Problem Document.pdf
├── Customer Behavior Dashboard.pbix
├── Customer Shopping Behavior Analysis.pdf
├── Customer-Shopping-Behavior-Analysis.pptx
├── Customer_Shopping_Behavior_Analysis_Project.ipynb
├── README.md
├── customer_behavior_sql_queries.sql
└── customer_shopping_behavior.csv