Patent ID: 11972446
Assignee: CAPITAL ONE SERVICES, LLC
Field: IT methods for management (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A method for predicting communication channels or communication timing based on user engagement, comprising:
obtaining, by a device, historical information associated with user engagement with one or more historical communications associated with a user account, wherein the one or more historical communications are associated with one or more services;
training, by the device, a machine learning model, using the historical information, to predict at least one of preferred communication channels, preferred communication timings, or preferred communication content associated with the user account for the one or more services, wherein the historical information includes:
a rate at which a user responds to the one or more historical communications, and
a successful delivery rate associated with the one or more historical communications;

determining, by the device, that a communication associated with the user account is to be transmitted, wherein the communication is associated with a service of the one or more services;
obtaining, from the machine learning model and by the device, recommendation information including at least one of a recommended timing, a recommended communication channel, or a recommended content of the communication based on providing information associated with the user account and the service to the machine learning model;
obtaining template content associated with the communication;
customizing the template content to obtain the content of the communication based on a recommendation received from the machine learning model,
wherein customizing the template content includes extracting time sensitive information that is specific to the user account and placing the time sensitive information at a start of the communication, and
wherein the communication includes other information after the time sensitive information;

generating, by the device, the communication according to the recommendation information;
receiving feedback information indicative of one or more events associated with user engagement with the communication; and
re-training the machine learning model using a feedback loop that includes providing the feedback information, and outputs of the machine learning model, to the machine learning model as inputs to re-train the machine learning model.