Granted Patent B2

US 8,565,410 · App. 13/843,541 · Granted Oct 22, 2013

Abstract

Claims (62)

1. A method, comprising:

obtaining, by one or more computers, agent parameter data for a set of agents;

ranking or percentiling, by the one or more computers, the agents based at least in part on the agent parameter data, to obtain an agent distribution of agent rankings or percentiles;

partitioning, by the one or more computers, callers in a set of callers based on one or more criteria into a set of partitions;

obtaining, by one or more computers, caller propensity data for the respective partitions;

ranking or percentiling, by the one or more computers, the callers based at least in part on data relating to or predicting a caller propensity for a desired outcome based at least in part on the caller propensity data for the partitions of the respective callers, to obtain a caller distribution of caller rankings or percentiles;

performing distribution compensation, by the one or more computers, using at least one algorithm selected from the group of:

an edge compensation algorithm applied to at least one selected from the group of the distribution of the agent rankings or percentiles and the distribution of the caller rankings or percentiles, near at least one edge of the respective distribution, to obtain edge compensated rankings or percentiles; and

a topology altering algorithm applied to either or both of the distribution of the agent rankings or percentiles and the distribution of the caller rankings or percentiles, to change one or more of the distributions to a different topology; and

matching, by the one or more computers, a respective one of the agents with a respective ranking or percentile to a respective one of the callers in one of the partitions with a closest respective ranking or percentile, where at least one of the caller ranking or percentile or the agent ranking or percentile has been distribution compensated.

2. The method as defined in claim 1 , wherein the performing the distribution compensation step uses the edge compensation algorithm and provides edge compensation only to the agent rankings or percentiles.

3. The method as defined in claim 1 , wherein the performing the distribution compensation step uses the edge compensation algorithm and provides edge compensation only to the caller rankings or percentiles.

4. The method as defined in claim 1 , wherein the performing the distribution compensation step uses the edge compensation algorithm and provides edge compensation to both the caller rankings or percentiles and the agent rankings or percentiles.

5. The method as defined in claim 1 , wherein the distribution compensation step uses the edge compensation algorithm and takes the agents that are free at runtime, and rescales the respective agent rankings or percentiles for these runtime available agents to provide more space/margin at the edges of the agent distribution.

6. The method as defined in claim 5 , wherein with the amount of the margin is based at least in part on a number of the agents that are free at runtime.

7. The method as defined in claim 1 , wherein the distribution compensation step uses the edge compensation algorithm and takes the callers in a queue or other grouping at runtime and rescales the respective caller propensity rankings or percentiles, to provide more space/margin at the edges of the distribution.

8. The method as defined in claim 7 , wherein the amount of the margin is based at least in part on a number of callers that are in the queue or in the grouping at runtime.

9. The method as defined in claim 1 , wherein the distribution compensation step uses the edge compensation algorithm and weights multiple of the agents free at runtime near at least one edge of the agent distribution and weights multiple of the callers near at least one edge of the caller distribution to increase utilization of the agents at the at least one edge of the agent distribution.

10. The method as defined in claim 1 , wherein the distribution compensation step uses the edge compensation algorithm and weights multiple of the agents free at runtime near both edges of the agent distribution or weights multiple of the callers near both edges of the caller distribution.

11. The method as defined in claim 1 , wherein the partition for the callers is based at least in part on ore or more selected from the group of demographic data, area code, zip code, NPANXX, VTN, geographic area, 800 number, and transfer number.

12. The method as defined in claim 1 , wherein the agent performance data comprises one or more selected from the group of sale, number of items sold per call, and revenue per call coupled with handle time.

13. The method as defined in claim 1 , wherein the topology altering algorithm is used and converts the distribution of the agent performances and/or the distribution of the caller to a circle topology.

14. The method as defined in claim 1 , wherein the topology altering algorithm is used and converts the distribution of the agent performances and the distribution of the caller to remove the edges of the distribution.

15. The method as defined in claim 1 , where there are multiple agents available and one caller, Kappa for the distribution of the agents is greater than 1.0.

16. The method as defined in claim 1 , where there are multiple callers and one agent, Rho applied to the callers in a queue is greater than 1.0.

17. A system, comprising:

one or more computers configured with program code that, when executed, causes performance of the steps:

obtaining, by the one or more computers, agent parameter data for a set of agents;

ranking or percentiling, by the one or more computers, the agents based at least in part on the agent parameter data, to obtain an agent distribution of agent rankings or percentiles;

partitioning, by the one or more computers, callers in a set of callers based on one or more criteria into a set of partitions;

obtaining, by one or more computers, caller propensity data for the respective partitions;

ranking or percentiling, by the one or more computers, the callers based at least in part on data relating to or predicting a caller propensity for a desired outcome based at least in part on the caller propensity data for the partitions of the respective callers, to obtain a caller distribution of caller rankings or percentiles;

performing distribution compensation, by the one or more computers, using at least one algorithm selected from the group of:

an edge compensation algorithm applied to at least one selected from the group of the distribution of the agent rankings or percentiles and the distribution of the caller rankings or percentiles, near at least one edge of the respective distribution, to obtain edge compensated rankings or percentiles; and

a topology altering algorithm applied to either or both of the distribution of the agent rankings or percentiles and the distribution of the caller rankings or percentiles to change one or more of the distributions to a different topology; and

matching, by the one or more computers, a respective one of the agents with a respective ranking or percentile to a respective one of the callers in one of the partitions with a closest respective ranking or percentile, where at least one of the caller ranking or percentile or the agent ranking or percentile has been distribution compensated.

18. The system as defined in claim 17 , wherein the performing the distribution compensation step uses the edge compensation algorithm and provides edge compensation only to the agent rankings or percentiles.

19. The system as defined in claim 17 , wherein the performing the distribution compensation step uses the edge compensation algorithm and provides edge compensation only to the caller rankings or percentiles.

20. The system as defined in claim 17 , wherein the performing the distribution compensation step uses the edge compensation algorithm and provides edge compensation to both the caller rankings or percentiles and the agent rankings or percentiles.

21. The system as defined in claim 17 , wherein the distribution compensation step uses the edge compensation algorithm and takes the agents that are free at runtime, and rescales the respective agent rankings or percentiles for these runtime available agents to provide more space/margin at the edges of the agent distribution.

22. The system as defined in claim 21 , wherein with the amount of the margin is based at least in part on a number of the agents that are free at runtime.

23. The system as defined in claim 17 , wherein the distribution compensation step uses the edge compensation algorithm and takes the callers in a queue or other grouping at runtime and rescales the respective caller propensity rankings or percentiles, to provide more space/margin at the edges of the distribution.

24. The system as defined in claim 23 , wherein the amount of the margin is based at least in part on a number of callers that are in the queue or in the grouping at runtime.

25. The system as defined in claim 17 , wherein the distribution compensation step uses the edge compensation algorithm and weights multiple of the agents free at runtime near at least one edge of the agent distribution and weights multiple of the callers near at least one edge of the caller distribution to increase utilization of the agents at the at least one edge of the agent distribution.

26. The system as defined in claim 17 , wherein the distribution compensation step uses the edge compensation algorithm and weights multiple of the agents free at runtime near both edges of the agent distribution or weights multiple of the callers near both edges of the caller distribution.

27. The system as defined in claim 17 , wherein the partition for the callers is based at least in part on ore or more selected from the group of demographic data, area code, zip code, NPANXX, VTN, geographic area, 800 number, and transfer number.

28. The system as defined in claim 17 , wherein the agent performance data comprises one or more selected from the group of sale, number of items sold per call, and revenue per call coupled with handle time.

29. The system as defined in claim 17 , wherein the topology altering algorithm is used and converts the distribution of the agent performances and/or the distribution of the caller to a circle topology.

30. The system as defined in claim 17 , wherein the topology altering algorithm is used and converts the distribution of the agent performances and the distribution of the caller to remove the edges of the distribution.

31. The system as defined in claim 16 , where there are multiple agents available and one caller, Kappa for the distribution of the agents is greater than 1.0.

32. The system as defined in claim 16 , where there are multiple callers and one agent, Rho applied to the callers in a queue is greater than 1.0.

33. A program product comprising:

a non-transitory computer-readable medium configured with computer-readable program code, that when executed, by one or more computers, causes the performance of the steps:

obtaining, by the one or more computers, agent parameter data for a set of agents;

ranking or percentiling, by the one or more computers, the agents based at least in part on the agent parameter data, to obtain an agent distribution of agent rankings or percentiles;

partitioning, by the one or more computers, callers in a set of callers based on one or more criteria into a set of partitions;

obtaining, by one or more computers, caller propensity data for the respective partitions;

ranking or percentiling, by the one or more computers, the callers based at least in part on data relating to or predicting a caller propensity for a desired outcome based at least in part on the caller propensity data for the partitions of the respective callers, to obtain a caller distribution of caller rankings or percentiles;

performing distribution compensation, by the one or more computers, using at least one algorithm selected from the group of:

an edge compensation algorithm applied to at least one selected from the group of the distribution of the agent rankings or percentiles and the distribution of the caller rankings or percentiles, near at least one edge of the respective distribution, to obtain edge compensated rankings or percentiles; and

a topology altering algorithm applied to either or both of the distribution of the agent rankings or percentiles and the distribution of the caller rankings or percentiles, to change one or more of the distributions to a different topology; and

matching, by the one or more computers, a respective one of the agents with a respective ranking or percentile to a respective one of the callers in one of the partitions with a closest respective ranking or percentile, where at least one of the caller ranking or percentile or the agent ranking or percentile has been distribution compensated.

Assignments (14)