Abstract: A method for logical view visualization of user behavior in a networked computer environment that includes sites that a user may visit and wherein the sites comprise pages that the user may view and/or resources that the user may request includes the step of collecting raw data representing user behavior which can include requesting resources, viewing pages and visiting sites by the user. This raw data is then refined or pre-processed into page views and visit data and stored in a data mart. Pages are clustered into super pages, and page to super page mappings reflecting the relationship between pages and super pages are stored in the data mart. An automated clustering means is applied to the page view, visit and super page data in the data mart to discover clusters of visits to define super visits having visit behavior characteristics. The visit data stored in the data mart is then scored against the super visit clusters to classify visits into super visits according to visit behavior characteristics.