Web mining is the most important application of data mining techniques to extract knowledge from web data including web document, hyperlinks between documents, usage logs of web sites etc. Web mining has been explored to a vast degree and different techniques have been proposed for a huge variety of applications that includes search engine enhancement, optimization of web services, Business Intelligence, B2B and B2C business etc. Most research on web mining has been from a �process-centric� point of view which defined web mining as a sequence of tasks. In this paper, we highlight the significance of studying the evolving nature of the web pattern analysis (WPA). Web usage mining is used to discover interesting user navigation patterns and can be applied to many real-world problems, such as improving web sites/pages. A Web usage mining system performs five major tasks: i) data collection ii) information filtering iii) pattern discovery iv) pattern analysis and visualization techniques, and v) Knowledge Query Mechanism (KQM). Each task is explained in detail and its related technologies are introduced. The web mining research is a converging research area from several research communities, such as database system, information retrieval, information extraction and artificial intelligence. In this paper we implement how web usage mining techniques can be applied for the customization i.e. web visualization