Machine learning-driven servicing interface

A non-transitory, computer-readable storage medium containing instructions that, when executed by one or more processors, cause the one or more processors to:

• identify a trained machine learning model associated with a user interacting with a business application;
• use the trained machine learning model to determine a probability that the user will engage in a specific activity while interacting with the business application;
• retrieve a business value factor for the specific activity;
• calculate a user intent score for a user intent regarding a user interaction with the business application, the user intent score including a combination of the probability that the user will engage in the specific activity while interacting with the business application and the business value factor;
• and
• reprogram the business application, based on the user intent score, to provide an update to information for the business application to present to the user.

A system comprising:

• a memory to store instructions;
• and
• processing circuitry, coupled with the memory, operable to execute the instructions that, when executed, enable the processing circuitry to:
• identify a trained machine learning model associated with a user interacting with a business application;
• use the trained machine learning model to determine a probability that the user will engage in a specific activity while interacting with the business application;
• retrieve a business value factor for the specific activity;
• calculate a user intent score for a user intent regarding a user interaction with the business application, the user intent score including a combination of the probability that the user will engage in the specific activity while interacting with the business application and the business value factor;
• and
• reprogram the business application, based on the user intent score, to provide an update to information for the business application to present to the user.