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Market response modelling is well covered in the marketing literature. However, much less research has been undertaken in the use of neural networks for market response modelling. Describes experiments to fit neural networks to the consumer goods market. Compares the neural network approach with several other possible models. Focuses on the out‐of‐sample performance of the models. Describes a method for adjusting the neural network architecture which leads to better performance on out‐of‐sample data.