Advertising Coverage Prediction Based on grp-reach Dual Parameter Model

Abstract

In today's era, the intelligent development trend of media is unstoppable. The rich media scattered the users' viewing media contacts, leading to the complexity of media advertising exposure and related effect evaluation and prediction. In this paper, this study use as simple a model as possible to predict the advertising coverage in the case of cross media platform data. On the basis of data processing, this paper proposes a prediction model of advertising coverage —— grp-reach dual parameter model. This model can better predict the advertising coverage. Compared with other traditional models, the goodness of fit increases by 0.08 on average, which is helpful to predict users' media consumption behavior. The model can also infer the investment required to increase another reach percentage point when the advertising cost is known, which can provide new ideas and strategies for advertising in sub media delivery, and provide decision-making reference for advertising delivery of different advertising companies.