As the rapid growth of World Wide Web nowadays, many companies tend to disseminate relevant information such as the introduction of product and service through their commercial Web sites. A company¡¦s Web site is deemed as a certain kind of its business assets. Customers, suppliers, partners, associations and other outsiders who desire to get access to the assets from the Web construct a company¡¦s external Web environment. From a strategic planning point of view, identifying a company¡¦s external environment helps to create its business values. Therefore, this research focuses on the issue of assisting a company to identify its external Web environment using mining techniques. Several research works pointed out that the hyperlink structure among Web pages could contribute to classifying the relationships within a company¡¦s external environment. We then propose a classifier that combines Web content mining and hyperlink structure, CNB-HI, for such a purpose. We apply our proposed approach to a real case to help identify the roles of customers, partners, media, and associations. Two experiments are conducted to examine the performance. In the first experiment, we compare CNB with other forms of Naïve Bayesian classifiers, and conclude that CNB achieves a better performance. However, even the performance by CNB is not satisfactory based exclusively on content classification. The second experiment is conducted to examine the benefits with hyperlink information incorporated (CNB-HI). The result shows that the performance of CNB-HI improves markedly. It thus justifies the feasibility of the proposed approach to real applications.