Communication response analyzer

A system comprising:

• a memory comprising instructions;
• and
• one or more computer processors, wherein the instructions, when executed by the one or more computer processors, cause the system to perform operations comprising:
• causing presentation in a first user interface (UI) of a message from a sender to a recipient, the message requesting a response from the recipient, the first UI including response options comprising:
• a first button to select a first classification;
• a second button to select a second classification;
• and
• a text entry field for entering a free text message;
• receiving a recipient response that includes a selection of:
• (a) either the first button or the second button and the free text message entered in the text entry field;
• generating a featurized recipient response vector based on the free text message and the selection;
• calculating, by an acceptance machine-learning (ML) model, a classification value of the recipient response from a plurality of classification values based on the featurized recipient response vector;
• and
• presenting, in a second UI for the sender, an indicator for the message and the calculated classification value, wherein the presentation in the second UI is based on the calculated classification value.

A non-transitory machine-readable storage medium including instructions that, when executed by a machine, cause the machine to perform operations comprising:

• causing presentation in a first user interface (UI) of a message from a sender to a recipient, the message requesting a response from the recipient, the first UI including response options comprising:
• a first button to select a first classification;
• a second button to select a second classification;
• and
• a text entry field for entering a free text message;
• receiving a recipient response that includes a selection of:
• (a) either the first button or the second button and (b) the free text message entered in the text entry field;
• generating a featurized recipient response vector based on the free text message and the selection;
• calculating, by an acceptance machine-learning (ML) model, a classification value of the recipient response from a plurality of classification values based on the featurized recipient response vector;
• and
• presenting, in a second UI for the sender, an indicator for the message and the calculated classification value, wherein the presentation in the second UI is based on the calculated classification value.