Automatic quality management of chat agents via chat bots

1. A method for automated quality management of agents of a contact center, the method comprising:

selecting, by a processor, a topic for interacting with a human agent of the contact center;

identifying, by the processor, a dialog tree associated with the selected topic; and

engaging, by the processor, in an automated communication session with the human agent based on the identified dialog tree, wherein the engaging of the automated communication session includes:

receiving, by the processor, an input from the human agent;

identifying, by the processor, a current node of the dialog tree associated with the input;

selecting, by the processor, an automated phrase to be output in response to identifying the current node; and

outputting, by the processor, the automated phrase.

2. The method of claim 1 , further comprising:

identifying, by the processor, a target agent input associated with the identified current node;

semantically comparing, by the processor, the agent input to the target agent input;

determining, by the processor, whether the agent input is semantically equivalent to the target agent input;

calculating, by the processor, a performance score for the human agent based on the determining; and

outputting, by the processor, feedback based on the determined performance score.

3. The method of claim 2 , wherein the feedback comprises a report summarizing the human agent's proficiencies and/or areas of improvement.

4. The method of claim 2 , further comprising:

invoking, by the processor, a coaching session for the human agent based on the feedback.

5. The method of claim 1 , wherein the automated phrase is selected from a plurality of phrases provided by human customers for a current dialog state during interactions with agents of the contact center, the interactions relating to the selected topic.

6. The method of claim 5 , wherein the selecting of the automated phrase further comprises:

identifying, by the processor, frequency of each of the plurality of phrases for the current dialog state; and

selecting, by the processor, one of the plurality of the phrases based on the identified frequency.

7. The method of claim 1 , wherein the topic is selected based on a criterion to be optimized by the contact center.

8. The method of claim 1 , wherein the topic is selected based on performance of the human agent during interactions with human customers relating to the topic.

9. The method of claim 1 , wherein the topic is selected based on performance of the human agent during previous automated communication sessions.

10. The method of claim 1 , wherein the automated communication session is a text based chat session.

11. A system for automated quality management of agents of a contact center, comprising:

a processor; and

a memory coupled to the processor and storing instructions that, when executed by the processor, cause the processor to:

select a topic for interacting with a human agent of the contact center;

identify a dialog tree associated with the selected topic; and

engage in an automated communication session with the human agent based on the identified dialog tree, wherein the engaging of the automated communication session includes:

receiving an input from the human agent;

identifying a current node of the dialog tree associated with the agent input;

selecting an automated phrase to be output in response to identifying the current node; and

outputing the automated phrase.

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

identify a target agent input associated with the identified current node;

semantically compare the agent input to the target agent input;

determine whether the agent input is semantically equivalent to the target agent input;

calculate a performance score for the human agent based on the determining; and

output feedback based on the determined performance score.

13. The system of claim 12 , wherein the feedback comprises a report summarizing the human agent's proficiencies and/or areas of improvement.

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

invoke a coaching session for the human agent based on the feedback.

15. The system of claim 11 , wherein the automated phrase is selected from a plurality of phrases provided by human customers for a current dialog state during interactions with agents of the contact center, the interactions relating to the selected topic.

16. The system of claim 15 , wherein the selecting of the automated phrase further comprises:

identifying frequency of each of the plurality of phrases for the current dialog state; and

selecting one of the plurality of the phrases based on the identified frequency.

17. The system of claim 11 , wherein the topic is selected based on a criterion to be optimized by the contact center.

18. The system of claim 11 , wherein the topic is selected based on performance of the human agent during interactions with human customers relating to the topic.

19. The system of claim 11 , wherein the topic is selected based on performance of the human agent during previous automated communication sessions.

20. The system of claim 11 , wherein the automated communication session is a text based chat session.