Sales forecasting and risk management under uncertainty in the media industry

In this work we propose a data-driven modelization approach for the management of advertising investments of a firm. First, we propose an application of dynamic linear models to the prediction of an economic variable, such as global sales, which can use information from the environment and the investment levels of the company in different channels. After we build a robust and precise model, we propose a metric of risk, which can help the firm to manage their advertisement plans, thus leading to a robust, risk-aware optimization of their revenue. The advertising industry represents an estimate of US$ 529.43 billion [4] and this quantity is likely to increase in the following years. In parallel, there has been a recent interest in the application of data-driven models in the context of forecasting and decision making in the marketing industry.