Techniques for behavioral pairing in a contact center system

Patent metadata

Field	Value
Publication number	US-9930180-B1
Application number	US-201715582223-A
Country	US
Kind code	B1
Filing date	Apr 28, 2017
Priority date	Apr 28, 2017
Publication date	Mar 27, 2018
Grant date	Mar 27, 2018

Abstract

Techniques for behavioral pairing in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a contact center system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, a plurality of agents available for connection to a contact; determining, by the at least one computer processor, a plurality of preferred contact-agent pairings among possible pairings between the contact and the plurality of agents; selecting, by the at least one computer processor, one of the plurality of preferred contact-agent pairings according to a probabilistic model; and outputting, by the at least one computer processor, the selected one of the plurality of preferred contact-agent pairings for connection in the contact center system.

First claim

The invention claimed is:

1. A method for behavioral pairing in a contact center system comprising:
determining, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, a plurality of agents available for connection to a contact;
determining, by the at least one computer processor, a plurality of preferred contact-agent pairings among possible pairings between the contact and the plurality of agents;
selecting, by the at least one computer processor, one of the plurality of preferred contact-agent pairings according to a probabilistic network flow model to apply an amount of agent utilization skew and to optimize performance of the contact center system, wherein the optimized performance of the contact center system is attributable to the probabilistic network flow model; and
outputting, by the at least one computer processor, the selected one of the plurality of preferred contact-agent pairings for connection in the contact center system.

2. The method of claim 1 , wherein the probabilistic network flow model is a network flow model for balancing agent utilization.

3. The method of claim 1 , wherein the probabilistic network flow model is a network flow model for optimizing an overall expected value of at least one contact center metric.

4. The method of claim 3 , wherein the at least one contact center metric is at least one of revenue generation, customer satisfaction, and average handle time.

5. The method of claim 1 , wherein the probabilistic network flow model is a network flow model constrained by agent skills and contact skill needs.

6. The method of claim 1 , wherein the probabilistic network flow model incorporates expected payoff values based on an analysis of at least one of historical contact-agent outcome data and contact attribute data.

7. A system for behavioral pairing in a contact center system comprising:
at least one computer processor communicatively coupled to and configured to operate in the contact center system, wherein the at least one computer processor is further configured to:
determine a plurality of agents available for connection to a contact;
determine a plurality of preferred contact-agent pairings among possible pairings between the contact and the plurality of agents;
select one of the plurality of preferred contact-agent pairings according to a probabilistic network flow model to apply an amount of agent utilization skew and to optimize performance of the contact center system, wherein the optimized performance of the contact center system is attributable to the probabilistic network flow model; and
output the selected one of the plurality of preferred contact-agent pairings for connection in the contact center system.

8. The system of claim 7 , wherein the probabilistic network flow model is a network flow model for balancing agent utilization.

9. The system of claim 7 , wherein the probabilistic network flow model is a network flow model for optimizing an overall expected value of at least one contact center metric.

10. The system of claim 9 , wherein the at least one contact center metric is at least one of revenue generation, customer satisfaction, and average handle time.

11. The system of claim 7 , wherein the probabilistic network flow model is a network flow model constrained by agent skills and contact skill needs.

12. The system of claim 7 , wherein the probabilistic network flow model incorporates expected payoff values based on an analysis of at least one of historical contact-agent outcome data and contact attribute data.

13. An article of manufacture for behavioral pairing in a contact center system comprising:
a non-transitory processor readable medium; and
instructions stored on the medium;
wherein the instructions are configured to be readable from the medium by at least one computer processor communicatively coupled to and configured to operate in the contact center system and thereby cause the at least one computer processor to operate so as to:
determine a plurality of agents available for connection to a contact;
determine a plurality of preferred contact-agent pairings among possible pairings between the contact and the plurality of agents;
select one of the plurality of preferred contact-agent pairings according to a probabilistic network flow model to apply an amount of agent utilization skew and to optimize performance of the contact center system, wherein the optimized performance of the contact center system is attributable to the probabilistic network flow model; and
output the selected one of the plurality of preferred contact-agent pairings for connection in the contact center system.

14. The article of manufacture of claim 13 , wherein the probabilistic network flow model is a network flow model for balancing agent utilization.

15. The article of manufacture of claim 13 , wherein the probabilistic network flow model is a network flow model for optimizing an overall expected value of at least one contact center metric.

16. The article of manufacture of claim 15 , wherein the at least one contact center metric is at least one of revenue generation, customer satisfaction, and average handle time.

17. The article of manufacture of claim 13 , wherein the probabilistic network flow model is a network flow model constrained by agent skills and contact skill needs.

18. The article of manufacture of claim 13 , wherein the probabilistic network flow model incorporates expected payoff values based on an analysis of at least one of historical contact-agent outcome data and contact attribute data.

Assignees

• Afiniti Ltd

Inventors

• Kan Ittai
• Klugerman Michael Richard
• Riley Blake Jay

Classifications

• G06Q10/06311 Primary

  Scheduling, planning or task assignment for a person or group · CPC title

• H04M2203/556

  Statistical analysis and interpretation · CPC title

• G06Q10/06315

  Needs-based resource requirements planning or analysis · CPC title

• H04M3/5232

  Call distribution algorithms · CPC title

• H04M2203/402

  Agent or workforce management · CPC title