Challenge
A growing e-commerce retailer was struggling with low conversion rates and high cart abandonment. Customers were having difficulty finding relevant products in their large catalog.
Solution
We implemented a personalized AI recommendation engine that analyzes customer behavior, purchase history, and browsing patterns to suggest relevant products. The system uses collaborative filtering and deep learning to understand customer preferences.
Results
- 35% increase in sales conversion rate
- 28% reduction in cart abandonment
- 42% increase in average order value
- 50% more repeat purchases
Technologies Used
Recommendation Systems, Machine Learning, Collaborative Filtering, Real-time Analytics