🛒 Customer-Purchase-Behaviour-Analysis

This project analyzes customer shopping behavior using real survey data. The goal is to understand how factors like age, income, product preferences, and emotional triggers-especially FOMO (Fear of Missing Out) - influence online purchasing decisions.

📊 Project Highlights

• Dataset : Survey data from 357 respondents
• Techniques Used : Exploratory Data Analysis (EDA), FOMO analysis
• Tools : Python (Pandas, Matplotlib, Seaborn), Jupyter Notebook, Excel

🔍 Key Insights

• Young adults (18–25) are the most active online shoppers.
• Myntra, Amazon and Flipkart are the most preferred platforms.
• FOMO plays a strong role in festival-time buying decisions.
• Clothes and electronics are top product choices.

📁 Files Included

• data/: Excel dataset used for analysis
• notebooks/: Jupyter Notebook with full EDA and FOMO analysis
• docs/: Final project report in PDF format
• presentations/: PowerPoint presentation for academic submission

👤 Author

Aditya Kumar Singh
adityasingh81201@gmail.com
B.Tech. (Hons.) (CSE- Data Science and Data Engineering)
Lovely Professional University, Jalandhar, Punjab, 144411

📘 License

This project is for academic use only.