📌 Overview
An end-to-end exploratory data analysis of 11,000+ customer transactions from an Indian e-commerce platform, uncovering regional spending patterns, demographic trends, and product category insights to support data-driven business decisions.
🎯 Objectives
- Identify top-performing states and geographic zones by revenue
- Analyze spending behavior across age groups, gender, and marital status
- Uncover highest revenue-generating product categories
- Profile customer demographics to support targeted marketing strategies
- Automate report generation for scalable insight delivery
🛠️ Tools & Technologies
- Python -> Core analysis and automation
- Pandas & NumPyData -> cleaning and transformation
- Matplotlib & Seaborn -> Data visualization
- GitHubVersion -> control and project hosting
📈 Visualizations
- Top 10 states by revenue
- Revenue split by age group and gender
- Top 10 product categories
- Geographic zone performance
- Revenue by customer occupation
- Gender and marital status breakdown
🔍 What the data says
- 💰 Total Revenue₹106.2M
- 📦 Total Orders27,981
- 👥 Unique Customers3,752
- 🛍️ Avg Order Value₹3,797
📊 Key Findings
- 📍 Uttar Pradesh is the highest revenue-generating state at ₹19.4M
- 👩 Female customers drive 70% of total revenue
- 🎯 26-35 age group is the highest spending demographic
- 🍔 Food is the top-selling product category
- 💻 IT Sector professionals are the biggest spenders by occupation
- 🗺️ Central Zone leads all geographic regions in revenue
💡 Business Recommendations
- Target 26-35 female demographic — highest spending segment, prioritize in marketing campaigns
- Double down on Uttar Pradesh & Central Zone — highest revenue regions with growth potential
- Expand Food & Auto categories — top performing, high repeat purchase potential
- Build loyalty programs for IT Sector & Healthcare professionals — highest value occupations