Modeling the Audience's Banner ad Exposure for Internet Advertising Planning

The negative binomial distribution (NBD) model, having long been applied in analyzing repeat behaviors, is proposed to serve as a banner ad exposure model and an empirical validation indicates that the model performs well in both data fitting and prediction.

Abstract

Exposure models focusing on reach and frequency where an audience is exposed to an ad message are the foundation of audience measurement. Given that a certain fundamental assumption of conventional exposure models is not relevant in the Internet advertising context, this paper suggests that the audience's on-line banner exposure can be best analyzed by its Web site visits. The negative binomial distribution (NBD) model, having long been applied in analyzing repeat behaviors, is proposed to serve as a banner ad exposure model. An empirical validation indicates that the model performs well in both data fitting and prediction.