Case Study
Titan Retail Group
AI-powered personalization engine driving conversion and customer lifetime value.
Retail & E-Commerce
18% faster checkout
Outcome
$42M incremental revenue
Quantified Impact
Challenge
Generic product recommendations left revenue on the table during peak seasons.
Strategy
Built a real-time recommendation service using collaborative filtering and contextual embeddings.
Execution
- • Ingested 5 years of transaction and behavioral data into a feature store.
- • Trained and deployed ranking models with A/B testing infrastructure.
- • Integrated into checkout flow with 50ms latency SLA.
Tech stack
MLflowFeastRedisPostgreSQLNext.js
Results
- • 18% faster average checkout time
- • 23% higher cart conversion
- • 15% increase in average order value
Testimonial
"The personalization doubled our peak-season capacity without scaling servers."
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