RECOMMENDATIONS & ADS
Recommendations and agentic analytics at eBay
A complementary-product recommender, reusable agentic analytics, and an eBay Live pacing simulator.
The challenge
Extend similar-item recommendations to complementary products, make fragmented Ads investigations faster, and compare budget-allocation policies under uncertain live-auction conditions.
My contribution
Jointly designed a mobile recommender using offline LLM-derived intent profiles, eBay embeddings, and a contextual bandit before retrieval and reranking. Originated the analytics framework with read-only SQL, permission, and PII checks; wrote its core, reviewed integration by three engineers, and coordinated deployment. Also built the eBay Live pacing simulator.
The outcome
The recommender's online A/B test delivered relative lifts of 10% CTR and 5% GMV on the tested surface. Other Ads teams forked and repurposed the analytics framework; users reported one representative investigation falling from 10 to 3 hours.
Areas of work
- Contextual bandits
- Recommender systems
- Agentic analytics