Estimating of Factors Influencing the Brewing Market by Using Decision Trees: A Case of Bulgaria

Abstract

This study examines the influence of key market factors - price, distribution, digital and non-digital advertising, atmospheric temperature and others on the sales of the brewing sector in Bulgaria. The monthly observations over nearly five years are analyzed for a major brand of beer. The data are modeled using the powerful data mining technique of Classification and Regression Trees (CART). The built models describe beer sales in relation to the studied factors with high goodness-of-fit statistics: coefficient of determination up to R2 = 94% and RMSE = 3.11. Cross-validation and holdout data sampling are used to assess the quality of obtained models. The models are applied for forecasting the volume of beer sales for one month ahead.