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Sales Forecasting Using Artificial Neural Networks

Listed author(s):
  • Marusia Ivanova

This paper is an attempt to introduce the essence and methodology of Artificial Neural Networks (ANN) in marketing. In order to outline the benefits of their analytical application in marketing management, it is demonstrated how to solve a predictive problem applying one of the most widely used types of ANN - Multi-Layered Feedforward Neural Network. Sales history data about four brands from the Fast Moving Consumer Goods sector in Bulgaria are used for the analysis. Time series are examined for presence of sparsity, outliers and nonstationarity, because these data characteristics can have a significant effect on the accuracy of predictions. It has been proven that ANN gives more accurate predictions in comparison with traditional methods, such as ARIMA and Exponential Smoothing.

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Article provided by Bulgarian Academy of Sciences - Economic Research Institute in its journal Economic Thought.

Volume (Year): (2005)
Issue (Month): 6 ()
Pages: 60-81

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Handle: RePEc:bas:econth:y:2005:i:6:p:60-81
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