Static recommendations limited engagement
Retail customers received repeated product recommendations across visits, reducing discovery and limiting personalization performance.
We deployed real-time adaptive personalization
The solution integrated with existing ecommerce platforms and adjusted recommendations dynamically based on live customer behavior within each session.
Reinforcement learning–driven recommendation engine
A Multi-Armed Bandit system using Thompson Sampling balanced exploration and exploitation across web and mobile channels, optimizing session-level decisioning without disrupting existing logic.
Measurable engagement and conversion lift
Adaptive personalization improved performance shortly after deployment, validating real-time decisioning at scale.
