Electronic, web-based commerce enables and demands the application of intelligent methods to analyze information collected from consumer web sessions. We propose a method of increasing the granularity of the user session analysis by isolating useful subsessions within web page access sessions, where each subsession represents a frequently traversed path indicating high-level user activity. The subsession approximates user state information as well as anticipated user activity, and as a result is useful for personalization and pre-caching.