Grab innovates with generative AI and secure data collaboration (ADM203)
Key Takeaways
Overview
AWS has been supporting advertising and marketing customers for over 17 years, providing a secure cloud computing environment with a broad choice and flexibility of purpose-built services and solutions.
A new customer persona has emerged in this industry - Commerce Media Networks, which are companies selling products and services that use transactional data to create more relevant experiences for their customer base through advertising.
Commerce Media Networks have a rich set of diverse intent and transaction signals beyond just purchases at a single retailer that can be used to enhance the customer experience and create value for advertisers.
Challenges and Solutions
Companies want to unify and protect their first-party signals while driving hyper-personalized experiences for their customers using ML and AI.
AWS Clean Rooms enable two or more companies to match, analyze, and collaborate on collective data to generate new insights without revealing underlying data or removing it from their own cloud environment.
AWS Entity Resolution enables customers to match, link, and enhance related records using configurable rules-based matching, ML-based matching, or partner matching.
Grab's Journey and Innovation
Grab is Southeast Asia's leading super app offering ride-hailing, deliveries, and mobile payments to millions of customers.
Grab's collaboration with AWS goes back to 2012, and they have recently migrated most of their data workloads to AWS, leading to operational efficiencies and cost reductions.
Grab utilizes a hyper-personalized approach to serve their customers, leveraging demographic information, purchase history, customer satisfaction, and engagement data.
Grab uses AWS Clean Rooms for secure data collaboration with partners, and they are heavily invested in generative AI to streamline processes and deliver personalized content at scale.
Grab's "Mystique" tool uses generative AI to create engaging content for their users at scale, reducing content generation time by up to 98.5% and increasing engagement rates by 25-50%.
Lessons Learned and Future Considerations
Effective change management is crucial for the smooth transition and successful adoption of new technologies.
Providing teams with the right tools and training enables them to adapt to new systems and drive continuous improvements.
Anticipating and measuring hallucinations and latency, as well as finding the right balance between bold bets and the status quo, are important considerations.
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