Making Every Shopper Feel Like a VIP — AI Personalization at Scale
[Global Retailer] — 12 markets, 4 languages, 50K+ SKUs
THE CHALLENGE
A cross-border retailer needed to deliver personalized shopping experiences across 12 markets with different languages, currencies, cultural preferences, and product assortments. Their one-size-fits-all approach was failing — conversion rates varied wildly across markets, and customers in different regions responded to completely different products, content, and promotions.
OUR APPROACH
We built PersonaLens — an AI personalization engine that dynamically adapts the entire shopping experience based on individual user behavior and market-specific patterns. The system personalizes product recommendations, homepage content, category ranking, search results, and promotional messaging in real-time across all 12 markets.
TECHNICAL HIGHLIGHTS
- Real-time personalization engine processing 2M+ user sessions per day
- Multi-language recommendation model handling 4 languages natively
- Contextual bandit algorithm for real-time content optimization
- Market-specific ML models that capture cultural purchasing patterns
- Integration with headless CMS for dynamic content delivery
Results
- 22% increase in conversion rate across all markets
- 18% higher average order value
- 45% improvement in customer engagement scores
- 30% reduction in bounce rate on personalized pages
- System now serves 2M+ personalized sessions daily
TECHNOLOGIES USED
- Python
- PyTorch
- FastAPI | React + Next.js
- Contentful CMS
- Redis
- Elasticsearch
- GCP (Vertex AI, BigQuery, Cloud Run)