Learning Based on Simulations of Interactions of a Customer Contact Center

• US 20160189558A1
• Filed: 12/31/2014
• Published: 06/30/2016
• Est. Priority Date: 12/31/2014
• Status: Abandoned Application

• Current Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Original Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Inventors: McGann, Conor, Eisner, Joe, Ristock, Herbert Willi Artur, Konig, Yochai, Zhakov, Vyacheslav
• Application Number:
  US14/588,331
• Publication Number:
  US 20160189558A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/016 After-sales
• CPC Class Codes: G09B 5/06 with both visual and audible presentation of the material to be studied

Abstract

A system and method for simulating an interaction between a customer and an agent of a customer contact center. A processor receives input conditions for simulating the interaction and generates a model of the customer based on the input conditions. The processor receives a first action from an agent device associated with the agent and updates a state of the simulation model based on the first action. The processor identifies a second action of the simulation model in response to the updated state, executes the second action, determines an outcome of the simulation, and provides the outcome to the agent device. In response to the outcome, the agent is prompted to take an action different from the second action.

Claims

1. A method for simulating an interaction between a customer and an agent of a customer contact center, the method comprising:

receiving, by a processor, input conditions for simulating the interaction;

generating, by the processor, a model of the customer based on the input conditions;

receiving, by the processor, a first action from an agent device associated with the agent;

updating, by the processor, a state of the simulation model based on the first action;

identifying, by the processor, a second action of the simulation model in response to the updated state;

executing, by the processor, the second action;

determining, by the processor, an outcome of the simulation; and

providing the outcome, by the processor, to the agent device, wherein in response to the outcome, the agent is prompted to take an action different from the second action.

2. The method of claim 1, wherein the simulation is invoked by a simulation controller accessible to the agent device for rehearsing a real interaction between the customer and the agent.

3. The method of claim 2 further comprising:

receiving, by the processor, feedback from the real interaction between the customer and the agent; and

modifying the model of the customer based on the feedback.

4. The method of claim 1, wherein the simulation is invoked by a simulation controller for training the agent for handling a particular type of interaction.

5. The method of claim 4, wherein the input conditions for generating the model of the customer are based on the particular type of interaction for which the agent is to be trained.

6. The method of claim 5, wherein the input conditions include an expected outcome of the simulation, the method further comprising:

comparing, by the processor, the outcome of the simulation with the expected outcome; and

generating a score for the agent based on the comparing.

7. The method of claim 1, further comprising:

predicting, by the processor, a customer intent, wherein the input conditions include the predicted customer intent.

8. The method of claim 1, wherein the identifying of the second action includes selecting the second action amongst a plurality of candidate actions.

9. The method of claim 7, wherein the input conditions include an objective of the interaction, and the second action is for achieving the objective.

10. The method of claim 1, wherein the prompting the agent to take an action different from the second action includes dynamically modifying, by the processor, an agent script used by the agent to guide the agent during a particular interaction.

11. A system for simulating an interaction between a customer and an agent of a customer contact center, the system comprising:

processor; and

memory, wherein the memory includes instructions that, when executed by the processor, cause the processor to;

receive input conditions for simulating the interaction;

generate a model of the customer based on the input conditions;

receive a first action from an agent device associated with the agent;

update a state of the simulation model based on the first action;

identify a second action of the simulation model in response to the updated state;

execute the second action;

determine an outcome of the simulation; and

provide the outcome to the agent device, wherein in response to the outcome, the agent is prompted to take an action different from the second action.

12. The system of claim 11, wherein the simulation is invoked by a simulation controller accessible to the agent device for rehearsing a real interaction between the customer and the agent.

13. The system of claim 12, wherein the instructions further cause the processor to:

receive feedback from the real interaction between the customer and the agent; and

modify the model of the customer based on the feedback.

14. The system of claim 11, wherein the simulation is invoked by a simulation controller for training the agent for handling a particular type of interaction.

15. The system of claim 14, wherein the input conditions for generating the model of the customer are based on the particular type of interaction for which the agent is to be trained.

16. The system of claim 15, wherein the input conditions include an expected outcome of the simulation, wherein the instructions further cause the processor to:

compare the outcome of the simulation with the expected outcome; and

generate a score for the agent based on the comparing.

17. The system of claim 11, wherein the instructions further cause the processor to:

predict a customer intent, wherein the input conditions include the predicted customer intent.

18. The system of claim 11, wherein the instructions that cause the processor to identify the second action include instructions that cause the processor to select the second action amongst a plurality of candidate actions.

19. The system of claim 17, wherein the input conditions include an objective of the interaction, and the second action is for achieving the objective.

20. The system of claim 11, wherein the instructions cause the processor to dynamically modify an agent script used by the agent to guide the agent during a particular interaction.

21. The system of claim 11 further comprising:

a clock for providing an output signal, wherein the output signal is included as part of the input conditions for simulating the interaction.