Systems and methods for identifying a behavioral target during a conversation
A conversation may be monitored in real time using a trained machine learning model. This real-time monitoring may detect attributes of a conversation, such as a conversation type, a state of a conversation, as well as other attributes that help specify a context of a conversation. Contextually appropriate behavioral targets may be provided by machine learning model to an agent participating in a conversation. In some embodiments, these “behavioral targets” are identified by applying a set of rules to the contemporaneously identified conversation attributes. The behavioral targets may be defined in advance prior to the start of a conversation. In this way, the machine learning model may be trained to associate particular behavioral target(s) with one or more conversation attributes (or collections of attributes). This facilitates the real-time monitoring of a conversation and contemporaneous guidance of an agent with machine-identified behavioral targets.
1. One or more non-transitory computer-readable media storing instructions, which when executed by one or more hardware processors, cause performance of operations comprising:
monitoring a conversation to detect attributes of the conversation in real-time;
determining a suggestion based on the attributes of the conversation;
determining a first activity level of a user interface associated with the conversation;
responsive to determining that the first activity level meets a threshold value, refraining from presenting the suggestion;
determining a second activity level of the user interface associated with the conversation;
responsive to determining that the second activity level does not meet the threshold value, presenting the suggestion; and
wherein the first activity level and the second activity level are based on one or both of a typing rate and an average cursor movement distance per unit time.
2. The media of claim 1 , wherein the suggestion includes one or more of: a prompt, a recommended statement, or a behavioral target for guiding the conversation toward an ultimate target conclusion of the conversation.
3. The media of claim 1 , wherein the first activity level and the second activity level are based on a rate of speech associated with the conversation.
4. The media of claim 1 , wherein the first activity level and the second activity level are based on a number of open user interface windows.
5. The media of claim 1 , further comprising:
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion outside of the region of the user interface in active use.
6. The media of claim 1 , further comprising:
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion within the region of the user interface in active use.
7. A method comprising:
monitoring a conversation to detect attributes of the conversation in real-time;
determining a suggestion based on the attributes of the conversation;
determining a first activity level of a user interface associated with the conversation;
responsive to determining that the first activity level meets a threshold value, refraining from presenting the suggestion;
determining a second activity level of the user interface associated with the conversation;
responsive to determining that the second activity level does not meet the threshold value, presenting the suggestion; and
wherein the first activity level and the second activity level are based on one or both of a typing rate and an average cursor movement distance per unit time.
8. The method of claim 7 , wherein the suggestion includes one or more of: a prompt, a recommended statement, or a behavioral target for guiding the conversation toward an ultimate target conclusion of the conversation.
9. The method of claim 7 , wherein the first activity level and the second activity level are based on a rate of speech associated with the conversation.
10. The method of claim 7 , wherein the first activity level and the second activity level are based on a number of open user interface windows.
11. The method of claim 7 , further comprising:
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion outside of the region of the user interface in active use.
12. The method of claim 7 , further comprising:
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion within the region of the user interface in active use.
13. A system comprising:
at least one device including a hardware processor;
the system being configured to perform operations comprising:
monitoring a conversation to detect attributes of the conversation in real-time;
determining a suggestion based on the attributes of the conversation;
determining a first activity level of a user interface associated with the conversation;
responsive to determining that the first activity level meets a threshold value, refraining from presenting the suggestion;
determining a second activity level of the user interface associated with the conversation;
responsive to determining that the second activity level does not meet the threshold value, presenting the suggestion; and
wherein the first activity level and the second activity level are based on one or both of a typing rate and an average cursor movement distance per unit time.
14. The system of claim 13 , wherein the first activity level and the second activity level are based on a rate of speech associated with the conversation.
15. The system of claim 13 , wherein the first activity level and the second activity level are based on a number of open user interface windows.
16. The system of claim 13 , further comprising:
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion outside of the region of the user interface in active use.
17. The system of claim 13 , further comprising:
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion within the region of the user interface in active use.
18. The media of claim 1 , wherein the typing rate is computed based on one or more of: characters per unit of time or words per unit of time.
19. The method of claim 7 , wherein the typing rate is computed based on one or more of: characters per unit of time or words per unit of time.
20. The system of claim 13 , wherein the typing rate is computed based on one or more of: characters per unit of time or words per unit of time.
21. One or more non-transitory computer-readable media storing instructions, which when executed by one or more hardware processors, cause performance of operations comprising:
monitoring a conversation to detect attributes of the conversation in real-time;
determining a suggestion based on the attributes of the conversation;
determining a first activity level of a user interface associated with the conversation;
responsive to determining that the first activity level meets a threshold value, refraining from presenting the suggestion;
determining a second activity level of the user interface associated with the conversation;
responsive to determining that the second activity level does not meet the threshold value, presenting the suggestion;
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion outside of the region of the user interface in active use.
22. A method comprising:
monitoring a conversation to detect attributes of the conversation in real-time;
determining a suggestion based on the attributes of the conversation;
determining a first activity level of a user interface associated with the conversation;
responsive to determining that the first activity level meets a threshold value, refraining from presenting the suggestion;
determining a second activity level of the user interface associated with the conversation;
responsive to determining that the second activity level does not meet the threshold value, presenting the suggestion;
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion outside of the region of the user interface in active use.
23. A system comprising:
at least one device including a hardware processor;
the system being configured to perform operations comprising:
monitoring a conversation to detect attributes of the conversation in real-time;
determining a suggestion based on the attributes of the conversation;
determining a first activity level of a user interface associated with the conversation;
responsive to determining that the first activity level meets a threshold value, refraining from presenting the suggestion;
determining a second activity level of the user interface associated with the conversation;
responsive to determining that the second activity level does not meet the threshold value, presenting the suggestion;
identifying a region of the user interface in active use; and
responsive to determining the second activity level does not meet the threshold value, presenting the suggestion outside of the region of the user interface in active use.