User intent graphs are a complex representation of user behavior, aiming to capture the purpose of a series of actions. By visualizing these interactions as points on a graph, it's possible to understand user uniqueness while maintaining anonymity. Graph theory provides a framework for representing data as networks of entities, enabling the analysis of relationships between nodes. This can be applied to various real-world problems, such as optimizing navigation and building recommendation engines. User intent graphs are built by defining nodes and edges that represent interactions between users and products, with the goal of inferring user intent. These graphs enable personalization in applications like search, recommendations, and journeys, by surfacing next best actions based on user intent.