Comprehensive customer behavior dataset with 40 unique features including purchase history, browsing patterns, customer lifetime value, loyalty tiers, payment methods, social engagement, and customer segmentation labels for advanced marketing analytics
This dataset contains customer purchase history, browsing behavior, product preferences, and customer segmentation labels. Perfect for customer segmentation, recommendation systems, and marketing analytics.
Complete purchase records including frequency, order values, and total purchases
Detailed browsing behavior data including time spent and device preferences
Customer preferences for different product categories and device types
Pre-labeled customer segments (High Value, Medium Value, Low Value)
Optimized for clustering models and machine learning algorithms
Perfect for customer lifetime value, churn prediction, and targeting
Calculated CLV for each customer based on purchase history
6 different payment method preferences (Credit, Debit, PayPal, etc.)
5-tier loyalty program (Bronze, Silver, Gold, Platinum, Diamond)
Email open rates, click-through rates, and newsletter subscription status
Social media engagement scores and social shares count
Customer satisfaction scores and average review ratings
5 geographic regions (North, South, East, West, Central)
Mobile app user identification and app engagement metrics
Cart abandonment rates and shopping behavior patterns
Discount usage percentage and coupon redemption counts
7 different referral sources (Google, Social Media, Email, etc.)
Wishlist item counts for each customer
Preferred shopping hours and session duration data
Preferred shipping methods (Standard, Express, Overnight, Same Day)
Product return rates and customer support interactions
Cross-category purchase counts and repeat purchase rates
Product review counts and customer support interaction history
Customer since (months) and customer retention metrics
Average session duration and pages per session metrics
| Customer ID | Age | Gender | Annual Income | Spending Score | Purchase Freq | Avg Order Value | Category | Device | Segment |
|---|
Comprehensive data analysis including exploratory data analysis, customer segmentation, purchasing behavior, and product preferences.
python analyze_customers.py
Advanced customer segmentation using K-Means, DBSCAN, and Hierarchical Clustering algorithms.
python customer_segmentation.py
25+ SQL queries for data analysis including segmentation, gender analysis, product preferences, device analysis, and advanced analytics.