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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