This workflow automates the critical, latency-sensitive decision of which ad to serve to a resolved viewer, eliminating manual campaign rules and siloed channel logic. It directly improves ad relevance and campaign ROI by using a unified customer profile to select the highest-propensity offer. The operational upside comes from preventing over-exposure through real-time frequency capping, which reduces ad waste and protects customer experience. Implementation requires a low-latency service querying a graph database like Neo4j or AWS Neptune, integrated with DSPs and ad servers via server-side APIs.




