Measuring advertisement effectiveness—a neural network approach

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This study aims to incorporate Artificial Neural Network (ANN) for measuring the effectiveness of the TV broadcast advertisements (toothpaste) by discovering important factors that influence the advertisement effectiveness. The information about the effects of each of these factors has been studied and it is used for measuring the advertisement effectiveness. Fifty attributes are examined to derive values from thirteen factors. These thirteen factors are used as input to ANN model. The data collected from 837 respondents are used for training and testing the ANN. The backpropagation algorithm is used for adjusting the weights in the ANN. Experimental results show that the ANN model achieves 99% accuracy for measuring the advertisement effectiveness.

论文关键词:Advertisement effectiveness,Artificial Neural Networks,Backpropagation algorithm

论文评审过程:Available online 3 October 2005.

论文官网地址:https://doi.org/10.1016/j.eswa.2005.09.014