Retargeting telecommunication service provider website users for content views using machine learning systems and methods

Abstract

Systems and methods for retargeting users of a telecommunication service provider's website. The retargeting system prioritizes users for retargeting by assessing likelihood that the user will convert to a customer based on session-level navigation flows, user historic session patterns, and consumer data. This information is used to create a training dataset that indicates whether the information is associated with converting or non-converting users. The training dataset is used to train a machine learning model to generate conversion scores indicating a likelihood that a user will convert to a customer and retargeting recommendations. The conversion scores and recommendations can be used prioritize users for retargeting via third-party services, such as websites, social media platforms, or messaging services. Using training data, accuracy of the machine learning model can be assessed. When accuracy of the machine learning model does not exceed a threshold accuracy, the system can be retrained.