This project analyzes the Customer Shopping Latest Trends Dataset from Kaggle, exploring shopping behaviors of 3,900 customers. Using Python in Google Colab, I performed data cleaning, SQL-style querying, and visualizations to derive actionable insights.

Executive Summary

Actionable Insights

• Age Demographics: Customers aged 25–35 dominate, making them prime targets for mid-range fashion campaigns.
• Payment Trends: Credit cards are the preferred payment method; explore exclusive card-based promotions.
• High-Value Categories: Clothing and footwear yield higher purchase amounts; prioritize inventory and marketing here.
• Seasonal Opportunities: Winter sees elevated spending; plan seasonal campaigns and flash sales.
• Review Influence: High review ratings correlate with repeat purchases; incentivize post-purchase reviews.
• Subscriber Value: Subscribers spend more frequently and at higher values; develop loyalty programs.

📈 Full Analysis Report

Explore the interactive report with detailed visualizations and data profiling:

Customer Shopping Trends Report