Graph databases and signal loss in AdTech

The deprecation of third-party cookies has led to significant signal loss in the AdTech industry, prompting professionals to rethink their strategies for reaching audiences at scale. As deterministic models become less reliable, companies are turning to probabilistic models and leveraging graph data models to represent both customers and their journeys. Graph databases offer a natural fit for identity resolution in AdTech, enabling richer, more sophisticated representations of identity that can improve targeting, attribution, and other imperatives such as Customer 360. To successfully transition to the post-deterministic identity resolution using graph data models and graph databases, businesses should follow a five-step process: define the business process/problem statement, know the data and draft the schema, write out the queries, create sample data and Gremlin queries, and scale, test, and optimize.