AI-Driven Personalization Engine for ShopSmart
Increased e-commerce revenue by 35% with an AI personalization engine serving 500K+ daily users.
The Challenge
ShopSmart's generic product recommendations were converting at 1.2% — well below industry average. They needed personalized experiences but lacked the ML infrastructure to build and serve recommendations at scale for 500K daily visitors.
Our Solution
We built a real-time recommendation engine using collaborative filtering and LLM-powered product descriptions. The system learns from every user interaction and serves personalized catalogs in under 50ms via a cached inference layer on Redis.
Our Approach
We designed a two-phase approach: first, a batch training pipeline running nightly on AWS SageMaker building user-item matrices; second, a real-time serving layer that blends batch scores with session context for instant recommendations.
Our e-commerce personalization engine built by TechVerse increased revenue by 35% in the first quarter. They understood our vision and executed flawlessly.
Project Details
Technologies Used
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Let's scope your project. We'll provide a fixed-price estimate and kick off within 48 hours — no obligation.
- US-based project manager from day 1
- Fixed-price — no scope creep surprises
- NDA signed before we discuss your idea
- 48-hour kickoff after contract