Machine Learning Recommendation Engine

An online retailer wanted to improve product recommendations to increase average order value and customer lifetime value, but had limited ML expertise in-house.

We built a machine learning recommendation engine using collaborative filtering and content-based algorithms. Trained models on historical data and deployed using AWS SageMaker with real-time inference capabilities.

Increased average order value by 22%, improved click-through rate on recommendations by 45%, reduced model retraining time from 1 week to 1 day.