🚀 Code Of Duty - Purchase Behaviour Analysis

A Comprehensive Exploratory Data Analysis (EDA) Project on Customer Purchase Behaviour.

---

📌 Project Overview

Customer Purchase Behaviour Analysis is a detailed data analysis project aimed at understanding and interpreting consumer behavior using Diwali sales data. The project explores key demographic and transactional attributes to uncover actionable business insights that can drive marketing, sales, and retention strategies.

🎯 Objectives

• Analyze customer purchase behavior patterns in a sales environment.
• Identify key factors influencing buying decisions.
• Segment customers based on purchasing habits.
• Discover cross-selling opportunities.
• Predict future purchasing trends.

---

🧠 Problem Statements

1. Customer Segmentation Challenge
   How can we effectively segment customers based on purchasing behavior to enable targeted marketing?

2. Purchase Pattern Uncertainty
   What hidden patterns exist in our customer purchase data that could inform product placement and promotional strategies?

3. Retention Rate Issues
   How can we identify customers at risk of churning before they stop purchasing?

4. Cross-selling Opportunities
   Which products are frequently purchased together, and how can we leverage this information?

5. Customer Lifetime Value Gap
   How can we predict and maximize the long-term value of different customer segments?

6. Seasonal Trend Analysis
   How do purchasing behaviors change over time, and how can we prepare for these fluctuations?

---

📁 Dataset

• Source: kaggle
• File: Diwali Sales Data.csv
• Key Columns:
  • user_name
  • customer_id
  • product_name
  • orders
  • gender
  • occupation
  • zone
  • marital_status
  • age_group
  • and more...

---

🛠️ Tools & Technologies Used

• Python
• Jupyter Notebook
• NumPy
• Pandas
• Matplotlib
• Seaborn
• Power BI

---

📊 Key Insight

• Married women aged 26–35 years from Uttar Pradesh, Maharashtra, and Karnataka, working in IT, Healthcare, and Aviation, are more likely to buy products from Food, Clothing, and Electronics categories.

---

📈 Visualizations

The project includes a wide range of insightful visualizations such as:

• Bar graphs
• Histograms
• Count plots
• Heatmaps
• And many more...

💬 All plots are accompanied by detailed comments for better understanding and interpretation.

---

📈 Power BI Dashboards

---

📂 Project Structure

📦 Code Of Duty - Purchase Behaviour Analysis/
├── Customer_Purchase_Behaviour_Analysis.ipynb
├── Diwali Sales Data.csv
├── LICENSE
├── Analysis_POWER_BI.pbix
├── POWER BI ANALYSIS CONCLUSION.docx
└── README.md

---

👥 Credits

Thanks to my amazing team members:

• Mahi Aggarwal
• Furquan Ahmad
• Shantanu Tripathi

And special thanks to Team GUVI for the opportunity to work on this project!

---

🧾 License

This project is licensed under the MIT License. See the LICENSE file for more details.

---

🌟 Project Status

📌 Completed as part of an academic Data Visualization project, evaluated on the basis of:

• Data Cleaning & Handling Missing Values
• Feature Selection & Engineering
• Data Integrity
• Summary Statistics & Insights
• Pattern Recognition
• Outlier Management
• Visual Representation

---