Call mapping systems and methods using variance algorithm (VA) and/or distribution compensation

• US 8,929,537 B2
• Filed: 10/21/2013
• Issued: 01/06/2015
• Est. Priority Date: 03/26/2012
• Status: Active Grant

• Current Assignee: Afiniti Ltd
• Original Assignee: Satmap International Holdings, Ltd.
• Inventors: Chishti, Zia, Kan, Ittai
• Primary Examiner(s): ADDY, THJUAN KNOWLIN
• Application Number:
  US14/059,248
• Publication Number:
  US 20140044255A1
• Time in Patent Office: 442 Days
• Field of Search: 379/265.11, 379/265.12, 379/266.01, 379/266.08, 379/265.01, 379/265.05, 379/265.1, 379/266.02
• US Class Current: 379/265.11
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: H04M 3/5158 in combination with automated outdialling systems devices for signalling identity of wanted subscriber H04M1/26
• CPC Class Codes: H04M 3/5232 Call distribution algorithms
• CPC Class Codes: H04M 3/5233 Operator skill based call distribution
• CPC Class Codes: H04M 3/5238 with waiting time or load prediction arrangements

Abstract

Method, system and program product, comprising: obtaining agent parameter data; percentiling agents based on the agent parameter data, to obtain an agent distribution of agent percentiles; partitioning callers based on criteria into partitions; obtaining caller propensity data; percentiling the callers based on propensity for an outcome to obtain a caller distribution; performing distribution compensation using one algorithm selected from an edge compensation algorithm applied to the distribution of agent percentiles or the distribution of the caller percentiles, near at least one distribution edge to provide edge compensation, and a topology altering algorithm applied to either or both of the agent distribution and the caller distribution to change one or more of the distributions to a different topology; and matching an agent to a caller in one of the partitions with a closest respective percentile, where one of the caller percentile or the agent percentile has been distribution compensated.

Claims

1. A method, comprising:

obtaining, by one or more computers, agent parameter data for a set of agents that are logged in to a call center;

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;

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, to obtain a caller distribution of caller rankings or percentiles;

performing distribution compensation, by the one or more computers, using 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

matching, by the one or more computers, a respective one of the agents to a respective one of the callers based at least in part on their respective rankings or percentiles, 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 to provide 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 to provide 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 to provide 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 to take the agents that are free at runtime, and to rescale 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 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 to take the callers in a queue or other grouping at runtime and to rescale 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 to weight multiple of the agents logged in at runtime near at least one edge of the agent distribution and to weight 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 to weight multiple of the agents free at runtime near both edges of the agent distribution or to weight multiple of the callers near both edges of the caller distribution.

11. The method as defined in claim 1, further comprising:

partitioning, by the one or more computers, the callers into a set of partitions, where the partitions for the callers are based at least in part on one or more selected from the group of demographic data, area code, zip code, NPANXX, VTN, geographic area, 800 number, and transfer number; and

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

wherein the ranking or percentiling of the callers is based at least in part on the caller propensity data for the partitions of the respective callers.

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 call handle time.

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

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

15. 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 that are logged in to a call center;

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;

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, to obtain a caller distribution of caller rankings or percentiles;

performing distribution compensation, by the one or more computers, using 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

matching, by the one or more computers, a respective one of the agents to a respective one of the callers based at least in part on their respective rankings or percentiles, where at least one of the caller ranking or percentile or the agent ranking or percentile has been distribution compensated.

16. The system as defined in claim 15, wherein the performing the distribution compensation step uses the edge compensation algorithm to provide edge compensation only to the agent rankings or percentiles.

17. The system as defined in claim 15, wherein the performing the distribution compensation step uses the edge compensation algorithm to provide edge compensation only to the caller rankings or percentiles.

18. The system as defined in claim 15, wherein the performing the distribution compensation step uses the edge compensation algorithm to provide edge compensation to both the caller rankings or percentiles and the agent rankings or percentiles.

19. The system as defined in claim 15, wherein the distribution compensation step uses the edge compensation algorithm to takes the agents that are logged in at runtime, and to rescale the respective agent rankings or percentiles for these runtime available agents to provide more space/margin at the edges of the agent distribution.

20. The system as defined in claim 19, wherein the amount of the margin is based at least in part on a number of the agents that are free at runtime.

21. The system as defined in claim 15, wherein the distribution compensation step uses the edge compensation algorithm to take the callers in a queue or other grouping at runtime and to rescale the respective caller propensity rankings or percentiles, to provide more space/margin at the edges of the distribution.

22. The system as defined in claim 21, 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.

23. The system as defined in claim 15, wherein the distribution compensation step uses the edge compensation algorithm to weight multiple of the agents free at runtime near at least one edge of the agent distribution and to weight 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.

24. The system as defined in claim 15, 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.

25. The system as defined in claim 15, wherein the one or more computers are configured with program code that, when executed, causes performance of the steps:

partitioning, by the one or more computers, the callers into a set of partitions, where the partitions for the callers are based at least in part on one or more selected from the group of demographic data, area code, zip code, NPANXX, VTN, geographic area, 800 number, and transfer number; and

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

wherein the ranking or percentiling of the callers is based at least in part on the caller propensity data for the partitions of the respective callers.

26. The system as defined in claim 15, wherein the agent performance data comprises one or more selected from the group of sale, number of items sold per call, and call handle time.

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

28. The system as defined in claim 15, where there are multiple callers and one agent, and Rho applied to the callers in a queue is greater than 1.0.

29. 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 that are logged in to a call center;

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;

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, to obtain a caller distribution of caller rankings or percentiles;

performing distribution compensation, by the one or more computers, using 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

matching, by the one or more computers, a respective one of the agents to a respective one of the callers based at least in part on their respective rankings or percentiles, where at least one of the caller ranking or percentile or the agent ranking or percentile has been distribution compensated.