IP Library Granted Patent US 8,068,598
Granted Patent B1
US 8,068,598 · App. 12/080,289 · Granted Nov 29, 2011

Automatic agent training system

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Quick Facts
Patent No.
US 8,068,598
App. No.
12/080,289
Granted
Nov 29, 2011
Kind
B1
Abstract

An exemplary method for training call center agents over a communications network using automatically selected training scenarios comprises the steps of obtaining confirmations of availability of a plurality of call center agents, determining a proctor based on proctor attributes stored in a database, selecting an agent from the plurality of agents, based on agent attributes stored in the database, to be trained by the proctor, automatically determining a training scenario based on the selected agent's attributes, and enabling the proctor and the agent to engage in the training scenario.

Claims (42)

1. A method for training call center agents over a communications network using automatically selected training scenarios, comprising:

(a) obtaining confirmations of availability of a plurality of call center agents;

(b) determining a proctor based on proctor attributes stored in a database;

(c) selecting an agent from the plurality of agents, based on agent attributes stored in the database, to be trained by the proctor;

(d) automatically determining a training scenario based on the selected agent's attributes; and

(e) enabling the proctor and the agent to engage in the training scenario.

2. The method of claim 1 , wherein said proctor is selected based on said proctor's past performance.

3. The method of claim 1 , wherein said proctor is selected from said plurality of call center agents.

4. The method of claim 1 , wherein said proctor is an interactive voice response unit.

5. The method of claim 1 , wherein said agent attributes include past call handling performance.

6. The method of claim 1 , wherein metrics for selecting an agent based on agent attributes are customizable.

7. The method of claim 1 , wherein said automatically determining includes dynamically generating a new training scenario.

8. The method of claim 1 , wherein said automatically determining includes dynamically selecting a pre-defined training scenario.

9. The method of claim 1 , wherein said enabling includes instructing an automatic call director to send appropriate software scripts to the proctor and the agent.

10. A system for training call center agents over a communications network using automatically selected training scenarios, comprising:

a web server interface configured to obtain confirmations of availability of a plurality of call center agents;

a proctor selector configured to determine a proctor based on proctor attributes stored in a database;

an agent selector configured to select an agent from the plurality of agents, based on agent attributes stored in the database, to be trained by the proctor;

a training scenario selector configured to automatically determine a training scenario based on the selected agent's attributes; and

a automatic call director interface configured to enable the proctor and the agent to engage in the training scenario.

11. The system of claim 10 , wherein said proctor is selected based on said proctor's past performance.

12. The system of claim 10 , wherein said proctor is selected from said plurality of call center agents.

13. The system of claim 10 , wherein said proctor is an interactive voice response unit.

14. The system of claim 10 , wherein said agent attributes include past call handling performance.

15. The system of claim 10 , wherein metrics for selecting an agent based on agent attributes are customizable.

16. The system of claim 10 , wherein said training scenario selector is further configured to dynamically generate a new training scenario.

17. The system of claim 10 , wherein said training scenario selector is further configured to dynamically select a pre-defined training scenario.

18. The system of claim 10 , wherein said automatic call director interface is further configured to instruct an automatic call director to send appropriate software scripts to the proctor and the agent.

19. A non-transitory computer-readable medium for training call center agents over a communications network using automatically selected training scenarios, comprising logic instructions that, if executed:

(a) obtain confirmations of availability of a plurality of call center agents;

(b) determine a proctor based on proctor attributes stored in a database;

(c) select an agent from the plurality of agents, based on agent attributes stored in the database, to be trained by the proctor;

(d) automatically determine a training scenario based on the selected agent's attributes; and

(e) enable the proctor and the agent to engage in the training scenario.

20. The computer-readable medium of claim 19 , wherein said proctor is selected based on said proctor's past performance.

21. The computer-readable medium of claim 19 , wherein said proctor is selected from said plurality of call center agents.

22. The computer-readable medium of claim 19 , wherein said proctor is an interactive voice response unit.

23. The computer-readable medium of claim 19 , wherein said agent attributes include past call handling performance.

24. The computer-readable medium of claim 19 , wherein metrics for selecting an agent based on agent attributes are customizable.

25. The computer-readable medium of claim 19 , wherein said logic instructions for automatically determine include logic instructions that, if executed, dynamically generate a new training scenario.

26. The computer-readable medium of claim 19 , wherein said logic instructions for automatically determining include logic instructions that, if executed, dynamically select a pre-defined training scenario.

27. The computer-readable medium of claim 19 , wherein said logic instructions for enable includes logic instructions that, if executed, instruct an automatic call director to send appropriate software scripts to the proctor and the agent.

Assignments (10)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 14, 2025
From: SL MIDCO 2, LLC; SL MIDCO 1, LLC; LO PLATFORM MIDCO, INC.; SERENOVA, LLC; LIFESIZE, INC.; TELESTRAT LLC; LIGHT BLUE OPTICS INC.; SERENOVA WFM, INC.
To: ENGHOUSE INTERACTIVE INC.
Reel/Frame 070932/0415 →
SECURITY INTEREST Recorded Mar 16, 2020
From: SERENOVA, LLC
To: WESTRIVER INNOVATION LENDING FUND VIII, L.P.
Reel/Frame 052126/0423 →
RELEASE OF SECURITY INTEREST IN PATENT COLLATERAL AT REEL/FRAME NO. 43855/0947 Recorded Mar 3, 2020
From: GOLDMAN SACHS SPECIALTY LENDING GROUP, L.P., AS COLLATERAL AGENT
To: SERENOVA, LLC, FORMERLY KNOWN AS LIVEOPS CLOUD PLATFORM, LLC; LO PLATFORM MIDCO, INC.; TELSTRAT LLC
Reel/Frame 052079/0941 →
SECURITY INTEREST Recorded Mar 2, 2020
From: SERENOVA, LLC; LIFESIZE, INC.; LO PLATFORM MIDCO, INC.
To: SILICON VALLEY BANK, AS ADMINISTRATIVE AGENT AND COLLATERAL AGENT
Reel/Frame 052066/0126 →
RELEASE OF SECURITY INTEREST Recorded Nov 3, 2017
From: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS AGENT
To: LO PLATFORM MIDCO, INC.; SERENOVA, LLC
Reel/Frame 044030/0105 →
SECURITY INTEREST Recorded Oct 13, 2017
From: SERENOVA, LLC, FORMERLY KNOWN AS LIVEOPS CLOUD PLATFORM, LLC; LO PLATFORM MIDCO, INC.; TELSTRAT LLC
To: GOLDMAN SACHS SPECIALTY LENDING GROUP, L.P., AS COLLATERAL AGENT
Reel/Frame 043855/0947 →
CHANGE OF NAME Recorded Mar 20, 2017
From: LIVEOPS CLOUD PLATFORM, LLC.
To: SERENOVA, LLC.
Reel/Frame 041653/0292 →
PATENT SECURITY AGREEMENT Recorded Dec 24, 2015
From: LO PLATFORM MIDCO, INC.; LIVEOPS CLOUD PLATFORM, LLC
To: WELLS FARGO BANK, NATIONAL ASSOCIATION
Reel/Frame 037372/0063 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 3, 2015
From: LIVEOPS, INC.
To: LIVEOPS CLOUD PLATFORM, LLC
Reel/Frame 036946/0577 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 2, 2008
From: RUSSI, DARIO; CHEN, QIAN
To: LIVEOPS, INC.
Reel/Frame 020786/0922 →