Granted Patent B1

US 11,050,881 · App. 16/853,108 · Granted Jun 29, 2021

Inventor: Philip McCann (Galway, IE)

Assignee: Avaya Management L.P.

H04M3/42382G06F40/30G06N20/00H04M3/4365H04M3/5191H04M3/5233

Abstract

Claims (56)

1. A method of managing contacts in a contact center, the method comprising:

receiving a text-based communication from a customer of the contact center;

analyzing the text-based communication to determine a relevancy associated with the text-based communication;

based on the analysis, determining a relevancy level to assign to the text-based communication;

tagging the text-based communication with a relevancy tag that identifies the determined relevancy level;

updating a priority associated with assigning the text-based communication to an agent of the contact center based on the relevancy tag;

assigning the text-based communication to the agent of the contact center;

storing the text-based communication with the relevancy tag in a database of text-based communications, wherein the text-based communication is also stored with at least one agent note associated therewith;

enabling a machine learning process to analyze the database of text-based communications; and

updating a data model used to automatically tag text-based communications with relevancy tags based on the analysis performed by the machine learning process.

2. The method of claim 1 , wherein the text-based communication comprises an email from the customer to the contact center.

3. The method of claim 1 , wherein the at least one agent note comprises an affirmation that the relevancy level identified by the relevancy tag is appropriate.

4. The method of claim 1 , wherein the at least one agent note comprises a change to the relevancy level identified by the relevancy tag.

5. The method of claim 1 , wherein the machine learning process performs a semantic and/or syntactic analysis of text contained in the text-based communication.

6. The method of claim 1 , further comprising:

updating a second data model used to automatically tag communications other than text-based communications based on the analysis performed by the machine learning process.

7. The method of claim 1 , further comprising:

receiving a second text-based communication from another customer of the contact center; and

automatically tagging the second text-based communication with a second relevancy tag that identifies a relevancy level determined by the data model.

8. A communication system, comprising:

a processor; and

computer memory storing data thereon that enables the processor to:

receive a text-based communication from a customer of the contact center;

analyze the text-based communication to determine a relevancy associated with the text-based communication;

based on the analysis, determine a relevancy level to assign to the text-based communication;

tag the text-based communication with a relevancy tag that identifies the determined relevancy level;

update a priority associated with assigning the text-based communication to an agent of the contact center based on the relevancy tag;

assign the text-based communication to the agent of the contact center;

store the text-based communication with the relevancy tag in a database of text-based communications, wherein the text-based communication is also stored with at least one agent note associated therewith;

enable a machine learning process to analyze the database of text-based communications; and

update a data model used to automatically tag text-based communications with relevancy tags based on the analysis performed by the machine learning process.

9. The communication system of claim 8 , wherein the text-based communication comprises an email from the customer to the contact center.

10. The communication system of claim 8 , wherein the at least one agent note comprises an affirmation that the relevancy level identified by the relevancy tag is appropriate.

11. The communication system of claim 8 , wherein the at least one agent note comprises a change to the relevancy level identified by the relevancy tag.

12. The communication system of claim 8 , wherein the machine learning process performs a semantic and/or syntactic analysis of text contained in the text-based communication.

13. The communication system of claim 8 , wherein the processor is further enabled to:

update a second data model used to automatically tag communications other than text-based communications based on the analysis performed by the machine learning process.

14. The communication system of claim 8 , wherein the processor is further enabled to:

receive a second text-based communication from another customer of the contact center; and

automatically tag the second text-based communication with a second relevancy tag that identifies a relevancy level determined by the data model.

15. A contact center, comprising:

a server comprising a processor and a message routing engine that is executable by the processor and that enables the processor to:

receive an email;

analyze the email to determine a relevancy associated with the email;

based on the analysis, determine a relevancy level to assign to the email;

tag the email with a relevancy tag that identifies the determined relevancy level;

update a priority associated with assigning the email to an agent based on the relevancy tag;

assign the email to the agent;

store the email with the relevancy tag in a database, wherein the email is also stored with at least one agent note associated therewith;

enable a machine learning process to analyze the database; and

update a data model used to automatically tag future text-based communications with relevancy tags based on the analysis performed by the machine learning process.

16. The contact center of claim 15 , wherein the processor is further enabled to automatically delete a future text-based communication having a relevancy tag that indicates SPAM.

17. The contact center of claim 15 , wherein the processor is further enabled to automatically change a priority of a future text-based communication having a relevancy tag that indicates no response is required.

18. The contact center of claim 15 , wherein the at least one agent note comprises an affirmation that the relevancy level identified by the relevancy tag is appropriate.

19. The contact center of claim 15 , wherein the at least one agent note comprises a change to the relevancy level identified by the relevancy tag.

20. The contact center of claim 15 , wherein the processor is further enabled to automatically reassign the email to a different pool of agents having a skill associated with the relevancy tag.

Assignments (9)

Cited By (3)

US 12,425,515 US 12,621,323 US 12,718,198