Analysis of message quality in a networked computer system

A system to improve the quality of composed electronic messages, the system comprising:

• a data processing system communicatively coupled to a plurality of client devices, the data processing system comprising one or more processors and a memory storing computer code instructions, which when executed by the one or more processors, cause the one or more processors to:
• obtain training data associated with a plurality of electronic messages and, for each electronic message of the plurality of electronic messages, said training data including a respective indication of whether or not the electronic message resulted in a respective response sent by a recipient of the electronic message;
• generate, using the training data, one or more machine learning models to predict a likelihood of a response to an electronic message based, at least in part, on a plurality of features of the electronic message;
• and
• provide the one or more machine learning models to predict, based on the plurality of features of the electronic message, a likelihood of a response to the electronic message.

A method for improving the quality of composed electronic messages, the method comprising:

• obtaining training data associated with a plurality of electronic messages and, for each electronic message of the plurality of electronic messages, said training data including a respective indication of whether or not the electronic message resulted in a respective response sent by a recipient of the electronic message;
• generating, using the training data, one or more machine learning models to predict a likelihood of a response to an electronic message based, at least in part, on a plurality of features of the electronic message;
• and
• providing the one or more machine learning models to predict, based on the plurality of features of the electronic message, a likelihood of a response to the electronic message.

A non-transitory computer-readable medium comprising code instructions stored thereon, the computer code instructions, when executed by one or more processors, cause the one or more processors to:

• obtain training data associated a plurality of electronic messages and, for each electronic message of the plurality of electronic messages, said training data including a respective indication of whether or not the electronic message resulted in a respective response sent by a recipient of the electronic message;
• generate, using the training data, one or more machine learning models to predict a likelihood of a response to an electronic message based, at least in part, on a plurality of features of the electronic message;
• and
• provide the one or more machine learning models to predict, based on the plurality of features of the electronic message, a likelihood of a response to the electronic message.