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

Summary

Grab’s Customer Data Platform (CDP) introduced Scenarios to address the limits of daily batch attributes for real-time personalization across marketing and user journeys. The capability combines Scribe event triggers, geo-fencing, optional historical CDP data, and predictive models, with a self-serve GUI for configuring and validating event sequences and APIs for programmatic management. Incoming events are processed through Flink, with historical data evaluated in StarRocks and outputs written to Kafka, Amphawa, or both for downstream consumption; configured Scenarios become available within an hour and are designed for latency under 15 seconds. More than 12 implementations are live, including a Grab Unlimited abandonment intervention that notified users 15 minutes after signup drop-off and produced over a 3% uplift in subscriber conversions versus non-real-time acquisition campaigns. Planned work includes scalable Scenario sharding, multiple output destinations, and delayed triggering.

Takeaways

1. 1

   Scenarios support real-time triggers based on Scribe events and geo-fencing, with optional enrichment from historical CDP attributes and pre-trained or custom predictive models.

2. 2

   The architecture uses Flink for event processing, StarRocks for historical data evaluation, and Kafka or Amphawa for synchronizing outputs to downstream services; target latency is under 15 seconds.

3. 3

   A Grab Unlimited signup-abandonment Scenario sent follow-up notifications after 15 minutes and achieved more than a 3% uplift in subscriber conversions versus non-real-time acquisition campaigns.