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Customer Behavior Analysis

📌 Project Overview

This project analyzes customer behavior to uncover patterns in purchasing, revenue distribution, and customer segmentation. The goal is to provide actionable insights for business decision-making.

🛠️ Tools & Technologies

  • Python (Pandas)
  • SQL
  • Power BI

📊 Key Analysis Performed

  • Revenue comparison by gender
  • Customer segmentation (New, Returning, Loyal)
  • Impact of discounts on purchasing behavior
  • Subscription vs non-subscription analysis
  • Top-performing products by category
  • Revenue contribution by age group

📈 Dashboard

Dashboard The Power BI dashboard provides interactive visualizations of key metrics such as:

  • Total revenue
  • Customer segmentation
  • Product performance
  • Subscription trends

📂 Project Files

  • customer_shopping_behavior.csv → Dataset
  • customer_behavior.sql → SQL queries
  • customer_behavior_dashboard.pbix → Power BI dashboard
  • Customer_Behavior_Analysis_Report.pdf → Final report

🔍 Key Insights

  • Loyal customers contribute significantly to total revenue
  • Subscribed customers tend to spend more
  • Discounts influence both low and high-value customers
  • A few products dominate sales across categories

🚀 Conclusion

This project demonstrates how data can be transformed into meaningful insights using data analysis and visualization tools.

👤 Author

Vishal Biswas

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Customer behavior analysis using Python (Pandas), SQL, and Power BI to uncover insights on revenue, segmentation, and purchasing patterns.

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