Joint learning of time-series models leveraging natural language processing

A computer program product, comprising a computer readable storage medium having program instructions embodied therewith, the program instructions being executable by a computer to cause the computer to perform a method comprising:

• utilizing a classifier machine learning model to identify metrics that are most relevant to whether customers will renew purchase orders;
• predicting respective risks of non-renewal for the purchase orders using the identified metrics;
• applying a tone analyzer natural language processing (NLP) model to determine current sentiments for respective customers;
• and
• recommending which of the respective customers to pursue with additional resources based the respectively determined sentiments and risks of non-renewal.

A system for maximizing renewals of purchase orders, the system comprising:

• one or more processors;
• and
• a memory communicatively coupled to the one or more processors;
• wherein the memory comprises instructions which, when executed by the one or more processors, cause the one or more processors to perform a method comprising:
• utilizing a classifier machine learning model to identify metrics that are most relevant to whether customers will renew purchase orders;
• predicting respective risks of non-renewal for the purchase orders using the identified metrics;
• applying a tone analyzer natural language processing (NLP) model to determine current sentiments for respective customers;
• and
• recommending which of the respective customers to pursue with additional resources based the respectively determined sentiments and risks of non-renewal.