TECHNOLOGIES FOR IMPLICIT FEEDBACK USING MULTI-FACTOR BEHAVIOR MONITORING
A method of providing implicit feedback using multi-factor behavior monitoring according to an embodiment includes receiving, by a computing system, a transcript of a conversation between an agent and a user, providing, by the computing system, at least one suggestion to the agent via an agent application based on the transcript of the conversation between the agent and the user, evaluating, by the computing system, data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning, and updating, by the computing system, a knowledge base model based on the evaluation of the data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning.
1 . A system for providing implicit feedback using multi-factor behavior monitoring, the system comprising:
a computing system comprising at least one first processor and at least one first memory having a first plurality of instructions stored thereon that, in response to execution by the at least one first processor, causes the computing system to:
receive a transcript of a conversation between an agent and a user;
provide at least one suggestion to the agent via an agent application based on the transcript of the conversation between the agent and the user;
evaluate data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning; and
update a knowledge base model based on the evaluation of the data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning.
2 . The system of claim 1 , wherein the first plurality of instructions further causes the computing system to analyze the transcript of the conversation between the agent and the user to find suggestion content related to the transcript; and
wherein to provide the at least one suggestion to the agent comprises to provide at least one suggestion to the agent that references the suggestion content related to the transcript.
3 . The system of claim 2 , further comprising an agent device having a display, at least one second processor, and at least one second memory having a second plurality of instructions stored thereon that, in response to execution by the at least one second processor, causes the agent device to execute the agent application to present the at least one suggestion to the agent on the display via a graphical user interface.
4 . The system of claim 3 , wherein the second plurality of instructions further causes the agent device to monitor agent interactions with the agent application.
5 . The system of claim 4 , wherein the agent interactions comprise one or more user interactions with elements of the graphical user interface.
6 . The system of claim 5 , wherein to evaluate the data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning comprises to evaluate times at which the at least one suggestion were displayed and times of the agent interactions with the agent application.
7 . The system of claim 1 , wherein to update the knowledge base model based on the evaluation of the data indicative of behaviors of the agents with respect to the at least one suggestion using machine learning comprises to rank each of the at least one suggestion.
8 . The system of claim 1 , wherein to receive the transcript of the conversation between the agent and the user comprises to receive transcribed messages of the conversation between the agent and the user in real time.
9 . A method of providing implicit feedback using multi-factor behavior monitoring, the method comprising:
receiving, by a computing system, a transcript of a conversation between an agent and a user;
providing, by the computing system, at least one suggestion to the agent via an agent application based on the transcript of the conversation between the agent and the user;
evaluating, by the computing system, data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning; and
updating, by the computing system, a knowledge base model based on the evaluation of the data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning.
10 . The method of claim 9 , further comprising analyzing the transcript of the conversation between the agent and the user to find suggestion content related to the transcript; and
wherein providing the at least one suggestion to the agent comprises providing at least one suggestion to the agent that references the suggestion content related to the transcript.
11 . The method of claim 10 , wherein the agent application is executed by an agent device of the agent; and
further comprising presenting the at least one suggestion to the agent via a graphical user interface displayed on the agent device via the agent application.
12 . The method of claim 11 , further comprising monitoring agent interactions with the agent application.
13 . The method of claim 12 , wherein the agent interactions comprise one or more user interactions with elements of the graphical user interface.
14 . The method of claim 13 , wherein evaluating the data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning comprises evaluating times at which the at least one suggestion were displayed on the agent device and times of the agent interactions with the agent application.
15 . The method of claim 9 , wherein updating the knowledge base model based on the evaluation of the data indicative of behaviors of the agents with respect to the at least one suggestion using machine learning comprises ranking each of the at least one suggestion.
16 . The method of claim 9 , wherein receiving the transcript of the conversation between the agent and the user comprises receiving transcribed messages of the conversation between the agent and the user in real time.
17 . One or more non-transitory machine readable storage media comprising a plurality of instructions stored thereon that, in response to execution by a system, causes the system to:
receive a transcript of a conversation between an agent and a user;
provide at least one suggestion to the agent via an agent application based on the transcript of the conversation between the agent and the user;
evaluate data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning; and
update a knowledge base model based on the evaluation of the data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning.
18 . The one or more non-transitory machine readable storage media of claim 17 , wherein the plurality of instructions further causes the system to analyze the transcript of the conversation between the agent and the user to find suggestion content related to the transcript; and
wherein to provide the at least one suggestion to the agent comprises to provide at least one suggestion to the agent that references the suggestion content related to the transcript.
19 . The one or more non-transitory machine readable storage media of claim 17 , wherein to evaluate the data indicative of behaviors of the agent with respect to the at least one suggestion using machine learning comprises to evaluate times at which the at least one suggestion were displayed on an agent device and times of the agent interactions with the agent application.
20 . The one or more non-transitory machine readable storage media of claim 17 , wherein to receive the transcript of the conversation between the agent and the user comprises to receive transcribed messages of the conversation between the agent and the user in real time.