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E-commerce
Personalized Recommendations Boost Revenue 34%
Deep learning recommendation engine delivering personalized product suggestions across web and mobile, driving 34% revenue increase.
Client: Online Fashion RetailerDuration: 5 months
34%
Revenue Increase
+52%
Click-through Rate
10M+
Products Recommended
<100ms
Response Time
The Challenge
The retailer struggled with low conversion rates and generic product recommendations that didn't resonate with individual shoppers across their 10M+ product catalog.
Our Solution
We built a deep learning recommendation system using collaborative filtering and content-based models, delivering real-time personalized suggestions based on browsing behavior, purchase history, and style preferences.
Key Results
Revenue per user increased by 34%
Click-through rate improved by 52%
Average order value increased by 18%
Customer engagement time up 40%
Tech Stack
TensorFlowRedisElasticsearchAWS SageMakerReact
"The personalization engine has completely transformed our customer experience. Our shoppers now discover products they love, and our revenue reflects that."
Chief Digital Officer
Online Fashion Retailer
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