Uplift Modelling Applied to a Chilean Retail Company with Siamese Neural Networks

Marketing is essential for the success of any company today, both to project itself abroad and to achieve its business objectives. The personalized approach to marketing plays a crucial role, enabling more effective interaction with potential customers and reducing errors in promotional campaigns. One way to improve personalized marketing is by using artificial intelligence to predict the effectiveness of campaigns in converting users to customers. In this study, the use of Siamese neural networks for elevation modelling in a Chilean online retail company is proposed. The results obtained using this model are presented, as well as the classical elevation modelling techniques. These results show that the Siamese neural network model achieves an increase of more than 30% compared to the area under the Qini curve, while also being competitive in other metrics. As future work, it is planned to obtain more real data to carry out a better validation of this proposal as well as to compare the model with other proposed neural networks.