Increased performance with neural nets - an example from the marketing domain

Abstract

This paper shows that artificial neural networks can exploit the temporal structure in the domain of marketing investments. Two architectures are compared; a tapped delay neural network and simple recurrent net. The performance is evaluated, and the method for extending it is suggested. The method uses a sensitivity analysis and identifies which input parameters that could be removed for increased performance.