Using Trained Machine-Learning Model to Generate User Interface Prompting User of an Online System to Use Different Conversion Channel

A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by a processor, cause the processor to perform steps comprising:

• receiving, via a network from a device associated with a user of an online system, a signal indicating an interaction by the user with one or more items via a first conversion channel of the online system;
• responsive to receiving the signal, retrieving, from a database of the online system or the device associated with the user, one or more candidate items for the user to convert via a second conversion channel of the online system that is different from the first conversion channel;
• accessing a candidate item evaluation machine-learning model of the online system, wherein the candidate item evaluation machine-learning model is trained, based on conversion data, to identify a likelihood of conversion of each of the one or more candidate items by the user when using the second conversion channel;
• applying the candidate item evaluation machine-learning model to output, based at least in part on information about the user and information about each of the one or more candidate items, a conversion score for each of the one or more candidate items that indicates the likelihood of conversion;
• responsive to the conversion score being above a threshold score, generating a user interface signal for prompting the user to use the second conversion channel for conversion of each of the one or more candidate items;
• and
• generating, based on the interface signal, a user interface at the device associated with the user prompting the user to use the second conversion channel for conversion of each of the one or more candidate items.

A computer system comprising:

• a processor;
• and
• a non-transitory computer-readable storage medium having instructions that, when executed by the processor, cause the computer system to perform steps comprising:
• receiving, via a network from a device associated with a user of an online system, a signal indicating an interaction by the user with one or more items via a first conversion channel of the online system;
• responsive to receiving the signal, retrieving, from a database of the online system or the device associated with the user, one or more candidate items for the user to convert via a second conversion channel of the online system that is different from the first conversion channel;
• accessing a candidate item evaluation machine-learning model of the online system, wherein the candidate item evaluation machine-learning model is trained, based on conversion data, to identify a likelihood of conversion of each of the one or more candidate items by the user when using the second conversion channel;
• applying the candidate item evaluation machine-learning model to output, based at least in part on information about the user and information about each of the one or more candidate items, a conversion score for each of the one or more candidate items that indicates the likelihood of conversion;
• responsive to the conversion score being above a threshold score, generating a user interface signal for prompting the user to use the second conversion channel for conversion of each of the one or more candidate items;
• and
• generating, based on the interface signal, a user interface at the device associated with the user prompting the user to use the second conversion channel for conversion of each of the one or more candidate items.