In this episode, we explore how Uber tackled the challenge of personalizing CRM communications at scale through contextual bandit strategies enhanced with generative AI embeddings, lightweight and powerful models like LinUCB and XGBoost, and smart decision augmentation with SquareCB. This work shows how data science can take a core business need—delivering relevant user communications—and build systems that adapt in near real time to maximize impact.
For more details, you can refer to their published tech blog, linked here for your reference: https://www.uber.com/blog/enhancing-personalized-crm