Automatic generation and modification of contact streams via machine-learning analytics

Abstract

In some embodiments, a contact stream is generated or modified based on configuration data received from a machine-learning model. Multiple contact items are selected for a contact stream, to be delivered to a user device via electronic communication channels. In addition, a success metric is identified indicating an engagement with the contact stream or an action performed following the engagement. A machine-learning model is applied to the contact items, where the machine-learning model is trained to identify relationships among actions in an online environment and configuration parameters that control delivery of contact streams. The machine-learning model provides an output indicating configuration data or a success probability for the contact stream. The configuration data includes configuration parameter values computed by the machine-learning model for achieving the identified success metric. The success probability indicates a probability computed by the machine-learning model for achieving the identified success metric.