How Grab is accelerating growth with real-time personalization using Customer Data Platform scenarios

This post details the evolution of Grab's CDP Scenarios feature, focusing on its technical architecture and impact. It introduces the self-serve GUI for marketers to define event triggers, configure geo-fencing, and incorporate historical attributes or predictive models. The technical architecture highlights real-time Flink processing for evaluating user historical data via StarRocks and performing predictions using pre-trained models. Outcomes are synced to Kafka or Amphawa (DynamoDB). The post also outlines future areas of exploration, including optimized Scenario sharding for scalable processing, enhanced signal distribution across multiple destinations, and advanced scheduling and delayed triggering.