The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Aug. 16, 2022

Filed:

May. 27, 2021
Applicant:

Intuit Inc., Mountain View, CA (US);

Inventors:

Talia Tron, Shefayim, IL;

Adi Shalev, Herzlia, IL;

Yehezkel Shraga Resheff, Tel Aviv, IL;

Elik Sror, Tel Aviv, IL;

Assignee:

Intuit Inc., Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04M 3/51 (2006.01); H04M 3/523 (2006.01); G06F 40/00 (2020.01); G06N 20/00 (2019.01); G06Q 10/06 (2012.01); H04M 3/42 (2006.01);
U.S. Cl.
CPC ...
H04M 3/5233 (2013.01); G06F 40/00 (2020.01); G06N 20/00 (2019.01); G06Q 10/06398 (2013.01); H04M 3/42221 (2013.01); H04M 3/5175 (2013.01); H04M 3/5237 (2013.01); H04M 2203/401 (2013.01); H04M 2203/551 (2013.01);
Abstract

Systems and methods for automatically assessing a quality of service for agents of a customer support system are disclosed. An example method may include retrieving historical conversations between the agents and users of the customer support system, receiving user comments for one or more of the historical conversations, identifying which of the received user comments includes keywords indicative of one or more quality of service attributes, generating transcripts of historical conversations associated with the identified user comments, training a machine learning model based at least in part on the generated transcripts and the user comments of the historical conversations associated with the identified user comments, providing a plurality of current conversations between agents and users of the customer support system to the trained machine learning model, and generating a behavioral score for each of the agents using the trained machine learning model.


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