Personalized Product Recommendations
Impact18% AOV increase
AOV Increase18%
CTR+35%
Products500K+
Overview
Built a hybrid recommendation system for an e-commerce platform to deliver personalized product suggestions. The system combines user behavior analysis with product attribute matching for relevant recommendations.
The Challenge
The platform had low cross-sell rates and customers were not discovering relevant products, leading to missed revenue opportunities.
The Solution
Implemented a hybrid approach using matrix factorization for collaborative filtering, embeddings for content similarity, and a real-time serving layer for instant recommendations across all touchpoints.
Key Results
18% increase in average order value
35% higher CTR on recommendations
Scaled to 500K+ products catalog
Tech Stack
PythonPyTorchAWS SageMakerRedisElasticsearchFastAPIDynamoDB