As third-party cookies become obsolete, the AdTech industry is facing significant challenges in tracking digital identities, prompting a shift toward probabilistic models and identity graphs to maintain effective advertising strategies. With major tech companies phasing out cookies, advertisers are losing traditional data signals, affecting identity resolution, personalization, targeting, and attribution. As a result, AdTech companies are exploring new methods, including the use of graph databases, to develop a more comprehensive view of customer behavior through identity graphs, which consolidate customer data from various sources into a unified profile. This approach allows marketers to create more personalized and effective campaigns, despite the lack of deterministic signals. The graph data model is particularly suitable for this purpose, offering a natural way to represent complex relationships and optimize ad spend. As the industry adapts to these changes, companies are focusing on leveraging first-, second-, and third-party data and adopting a "layer cake approach" to address signal loss challenges, with graph databases playing a crucial role in this transition.