System and method of automated routing and guidance based on continuous customer and customer service representative feedback
The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.
1. A method for routing based on client sentiment, comprising:
generating the client sentiment for an incoming communication based on an analysis of the incoming communication;
selecting at least one customer service representative (CSR) designation to receive the incoming communication based on the client sentiment and a set of routing analytics rules (RAR);
performing an analysis of the set of RAR based on the client sentiment and the selected at least one CSR designation; and
updating the set of RAR based on the analysis.
2. The method of claim 1 , further comprising providing a customer engagement center system, the customer engagement center system is configured to receive incoming communications from outside of the customer engagement center system.
3. The method of claim 2 , further comprising receiving the incoming communication at the customer engagement center.
4. The method of claim 1 , wherein the client sentiment is generated as a set of communication metadata.
5. The method of claim 4 , wherein the selecting at least one customer service representative designation is also based on the set of communication metadata including the client sentiment.
6. The method of claim 1 , wherein the at least one customer service representative designation is at least one of a CSR, a CSR group, a queue, or a queue group.
7. The method of claim 1 , the method further comprising providing at least one of the incoming communication or the client sentiment to the customer service representative designation.
8. A system for routing based on client sentiment, the system comprising:
a processor, and
a memory comprising computer readable instructions that upon execution by the processor causes the system to:
generate the client sentiment for an incoming communication based on an analysis of the incoming communication;
select at least one customer service representative (CSR) designation to receive the incoming communication based on the client sentiment and a set of routing analytics rules (RAR);
perform an analysis of the set of RAR based on the client sentiment and the selected at least one CSR designation; and
update the set of RAR based on the analysis.
9. The system of claim 8 , wherein the system further comprises a customer engagement center system, the customer engagement center system is configured to receive incoming communications from outside of the customer engagement center system.
10. The system of claim 9 , wherein the processor further causes the system to receive the incoming communication at the customer engagement center.
11. The system of claim 8 , wherein the client sentiment is generated as a set of communication metadata.
12. The system of claim 11 , wherein the selection of at least one customer service representative designation is also based on the set of communication metadata including the client sentiment.
13. The system of claim 8 , wherein the at least one customer service representative designation is at least one of a CSR, a CSR group, a queue, or a queue group.
14. The system of claim 8 , wherein the processor further causes the system to provide at least one of the incoming communication or the client sentiment to the customer service representative designation.
15. A non-transitory computer readable medium programmed with computer readable code including instructions that when executed by a processor of a system, causes the system to execute a method for routing based on client sentiment comprising:
generate the client sentiment for an incoming communication based on an analysis of the incoming communication;
select at least one customer service representative (CSR) designation to receive the incoming communication based on the client sentiment and a set of routing analytics rules (RAR);
perform an analysis of the set of RAR based on the client sentiment and the selected at least one CSR designation; and
update the set of RAR based on the analysis.
16. The non-transitory computer readable medium of claim 15 , wherein the method to be executed further comprises provide a customer engagement center system, the customer engagement center system is configured to receive incoming communications from outside of the customer engagement center system.
17. The non-transitory computer readable medium of claim 16 , wherein the method to be executed further comprises receive the incoming communication at the customer engagement center.
18. The non-transitory computer readable medium of claim 15 , wherein the client sentiment is generated as a set of communication metadata.
19. The non-transitory computer readable medium of claim 18 , wherein the selection of at least one customer service representative designation is also based on the set of communication metadata including the client sentiment.
20. The non-transitory computer readable medium of claim 15 , wherein the at least one customer service representative designation is at least one of a CSR, a CSR group, a queue, or a queue group.