6533b858fe1ef96bd12b6ddd

RESEARCH PRODUCT

Application of neural network to predict purchases in online store

subject

description

A key ability of competitive online stores is effective prediction of customers’ purchase intentions as it makes it possible to apply personalized service strategy to convert visitors into buyers and increase sales conversion rates. Data mining and artificial intelligence techniques have proven to be successful in classification and prediction tasks in complex real-time systems, like e-commerce sites. In this paper we proposed a back-propagation neural network model aiming at predicting purchases in active user sessions in a Web store. The neural network training and evaluation was performed using a set of user sessions reconstructed from server log data. The proposed neural network was able to achieve a very high prediction accuracy of 99.6 % and recall of 87.8 %.