Retail & E-Commerce

Personalization Engine for ShopSphere

ShopSphere

47% CLV Increase

The Challenge

ShopSphere's generic product recommendations were generating click-through rates 40% below industry benchmarks and contributing to high cart abandonment.

Our Solution

We architected a real-time collaborative filtering engine augmented with session-aware contextual signals, deployed as a microservice with sub-20ms p99 latency at 8,000 requests per second.

Results

Customer lifetime value increased 47% in the 6 months post-launch. CTR on recommendations improved 3.2x. The ShopSphere team now owns and extends the system independently following our knowledge transfer program.

ShopSphere knew their customers deserved better recommendations. We built a personalization engine that learns from both historical behavior and real-time session signals — understanding not just what a customer has bought, but what they are looking for right now.

The system balances exploration and exploitation using a contextual bandit approach, ensuring new products get visibility while personalization accuracy continuously improves. A/B testing infrastructure was included in the delivery so the ShopSphere team can validate future model updates with confidence.

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