Call mapping systems and methods using bayesian mean regression (BMR)
Methods, systems, and articles of manufacture for ranking individuals in a contact center system including ranking a first individual in a set of individuals based on relative amounts of data for the first individual and one or more other individuals in the set of individuals.
1. A method for pairing in a contact center system comprising:
retrieving, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, a plurality of historical outcomes associated with a first agent of a plurality of agents in the contact center system;
determining, by the at least one computer processor, a first performance measurement of the first agent based on the plurality of historical outcomes;
determining, by the at least one computer processor, a first adjusted performance measurement by adjusting the first performance measurement based on a size of the plurality of historical outcomes; and
selecting, by the at least one computer processor, the first agent for pairing with a contact in the contact center system based at least in part on the first adjusted performance measurement.
2. The method of claim 1 , wherein the adjusting further comprises:
determining, by the at least one computer processor, a group performance measurement of the plurality of agents; and
weighting, by the at least one computer processor, the first performance measurement and the group performance measurement based on the size of the plurality of historical outcomes associated with the first agent.
3. The method of claim 2 , wherein the group performance measurement is a mean performance measurement across the plurality of agents.
4. The method of claim 3 , wherein the weighting is a regression to the mean performance measurement.
5. The method of claim 1 , where the adjusting further comprises:
applying, by the at least one computer processor, Bayesian mean regression to the first performance measurement to determine the first adjusted performance measurement.
6. The method of claim 1 , wherein the size of the plurality of historical outcomes is relatively small, and wherein a difference between the first performance measurement and the first adjusted performance measurement is relatively large.
7. The method of claim 1 , further comprising:
ranking, by the at least one computer processor, the plurality of agents based on respective adjusted performance measurements of each of the plurality of agents.
8. A system for 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:
retrieve a plurality of historical outcomes associated with a first agent of a plurality of agents in the contact center system;
determine a first performance measurement of the first agent based on the plurality of historical outcomes;
determine a first adjusted performance measurement by adjusting the first performance measurement based on a size of the plurality of historical outcomes; and
select the first agent for pairing with a contact in the contact center system based at least in part on the first adjusted performance measurement.
9. The system of claim 8 , wherein the at least one computer processor is further configured to adjust the first performance measurement by:
determining a group performance measurement of the plurality of agents; and
weighting the first performance measurement and the group performance measurement based on the size of the plurality of historical outcomes associated with the first agent.
10. The system of claim 9 , wherein the group performance measurement is a mean performance measurement across the plurality of agents.
11. The system of claim 10 , wherein the weighting is a regression to the mean performance measurement.
12. The system of claim 8 , wherein the at least one computer processor is further configured to adjust the first performance measurement by:
applying Bayesian mean regression to the first performance measurement to determine the first adjusted performance measurement.
13. The system of claim 8 , wherein the size of the plurality of historical outcomes is relatively small, and wherein a difference between the first performance measurement and the first adjusted performance measurement is relatively large.
14. The system of claim 8 , wherein the at least one computer processor is further configured to:
rank the plurality of agents based on respective adjusted performance measurements of each of the plurality of agents.
15. An article of manufacture for 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:
retrieve a plurality of historical outcomes associated with a first agent of a plurality of agents in the contact center system;
determine a first performance measurement of the first agent based on the plurality of historical outcomes;
determine a first adjusted performance measurement by adjusting the first performance measurement based on a size of the plurality of historical outcomes; and
select the first agent for pairing with a contact in the contact center system based at least in part on the first adjusted performance measurement.
16. The article of manufacture of claim 15 , wherein the at least one computer processor is further caused to adjust the first performance measurement by:
determining a group performance measurement of the plurality of agents; and
weighting the first performance measurement and the group performance measurement based on the size of the plurality of historical outcomes associated with the first agent.
17. The article of manufacture of claim 16 , wherein the group performance measurement is a mean performance measurement across the plurality of agents.
18. The article of manufacture of claim 17 , wherein the weighting is a regression to the mean performance measurement.
19. The article of manufacture of claim 15 , wherein the at least one computer processor is further caused to adjust the first performance measurement by:
applying Bayesian mean regression to the first performance measurement to determine the first adjusted performance measurement.
20. The article of manufacture of claim 15 , wherein the size of the plurality of historical outcomes is relatively small, and wherein a difference between the first performance measurement and the first adjusted performance measurement is relatively large.