10,000 synthetic customer profiles, 120,000 transaction records, and 25,000 product reviews. These relational files facilitate the simulation of e-commerce user journeys including demographic profiling, purchase history, and sentiment feedback.
Use Cases
- Train a recommendation engine using customer records and transaction logs
- Build a sentiment analysis model using the 25,000 product reviews
- Calculate customer lifetime value (CLV) based on the 120,000 transaction records
- Segment users by linking customer profiles to their specific transaction history
Strengths
- 10,000 unique customer profiles for demographic segmentation
- 120,000 transaction records for longitudinal purchase behavior analysis
- 25,000 text-based reviews for natural language processing