AI-powered personalization engine for e-commerce
+23%
Conversion rate increase
+18%
Average order value
<100ms
Recommendation latency
2M+
Monthly visitors served
The challenge
A mid-market e-commerce retailer with 2M+ monthly visitors was showing the same product recommendations to everyone. Conversion rates were flat despite growing traffic.
Our solution
We built a real-time personalization engine that combines collaborative filtering, content-based recommendations, and contextual bandits. The system serves personalized product recommendations, search re-ranking, and dynamic homepage content — all updating in real-time based on user behavior.
Key highlights
Real-time signals
User behavior updates recommendations instantly
Multi-model ensemble
Collaborative + content-based + contextual bandits
Search re-ranking
Personalized search results per user profile
Dynamic homepage
Content adapts to each visitor in real time
Tech stack
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