Abstract: Systems and methods of generating, for display on a graphical user interface (GUI), a personalized advertisement. The systems and methods can include receiving data indicative of initiating a browsing session, aggregating user activity data associated with a user of the application, the user activity data including current session data and/or past session data, applying machine learning on the user activity data to generate one or more excluded products, applying the one or more excluded products to a product database to generate a list of relevant products, ranking, using one or more ranking rules, the list of relevant products to generate a ranked list of relevant products, and sending, to the mobile device, the personalized advertisement including one or more relevant products from the ranked list of relevant products.

Abstract: Systems and methods of generating, for display on a graphical user interface (GUI), a personalized advertisement. The systems and methods can include receiving data indicative of initiating a browsing session, aggregating user activity data associated with a user of the application, the user activity data including current session data and/or past session data, applying machine learning on the user activity data to generate one or more excluded products, applying the one or more excluded products to a product database to generate a list of relevant products, ranking, using one or more ranking rules, the list of relevant products to generate a ranked list of relevant products, and sending, to the mobile device, the personalized advertisement including one or more relevant products from the ranked list of relevant products.

Abstract: A method for targeting advertising includes receiving, at a first server, customer action information associated with the customer, and receiving a plurality of advertising campaigns. The method also includes generating, using a first algorithm, a list of products derived from the customer action information that the customer may have interest in over a first time period, and generating, using a second algorithm, a ranked list of product categories derived from the customer action information that, if purchased by the customer, would generate a highest amount of revenue over a second time period. The method further includes sending a first communication associated with a first advertising campaign of the plurality of advertising campaigns to a customer device, the first advertising campaign chosen by a third algorithm that incorporates, as input, the list of products and the ranked list of product categories.