In this paper, we present an integrated framework for the optimization of Internet banner advertising. The framework consists of three parts: statistical predictive modeling on web data, optimization through mixed integer programming, and the use of information repository technology. The integrated, quantitative approach allows for the automatic improvement of banner advertising strategies and nonintrusive personalized advertising at a variety of banner display levels.