Automated systems for communications analysis according to recording restrictions
Disclosed embodiments provide a framework for automatically establishing recording parameters according to specified recording restrictions and generating analytics corresponding to communications recorded subject to the recording restrictions. During a communications session between a user and an agent, a system can identify any recording restrictions corresponding to user communications exchanged during the communications session. The system automatically processes, in real-time, communications exchanged during the communications session as these communications are exchanged to identify the user communications and agent communications. The system generates a transcript that includes the agent communications but selectively records and transcribes the user communications according to the recording restrictions. A machine learning algorithm is trained to generate a set of inferences corresponding to a user sentiment based on historic recordings and transcripts of historic communications sessions between users and agents, as well as corresponding feedback. From the set of inferences, the system generates agent analytics.
1. A computer-implemented method, comprising:
dynamically processing, in real-time, communications exchanged during a communications session between a user and an agent to isolate user communications associated with the user, wherein the communications session is associated with an intent;
continuously generating a recording, wherein the recording includes the user communications and agent communications associated with the agent, and wherein the recording is generated according to an affirmative user consent;
detecting a revocation of the affirmative user consent during the communications session, wherein the revocation is communicated through a new user communication exchanged during the communications session;
automatically removing the user communications from the recording such that the recording is devoid of the user communications and any subsequent user communications exchanged during the communications session;
dynamically training a machine learning algorithm to generate a set of inferences corresponding to user sentiment associated with the intent, wherein the machine learning algorithm is dynamically trained using historic recordings corresponding to historic communications sessions between users and agents, and feedback corresponding to the historic communications sessions;
processing the agent communications from the recording through the machine learning algorithm to generate the set of inferences; and
generating agent analytics corresponding to the intent, wherein the agent analytics are generated based on the set of inferences and the recording.
2. The computer-implemented method of claim 1 , wherein automatically removing the user communications from the recording further includes:
inserting one or more audial nulls in the recording to replace the user communications.
3. The computer-implemented method of claim 1 , wherein generating the agent analytics includes:
identifying a set of agent training needs, wherein the set of agent training needs correspond to actions performable to improve agent responses to intents.
4. The computer-implemented method of claim 1 , wherein detecting the revocation of the affirmative user consent further includes:
processing the new user communication as the new user communication is exchanged during the communications session; and
detecting one or more anchor terms corresponding to a request to cease recording of the user communications.
5. The computer-implemented method of claim 1 , further comprising:
calculating a voice signature associated with the agent, wherein the voice signature is calculated during an onboarding process; and
identifying the user communications based on the user communications not corresponding to the voice signature.
6. The computer-implemented method of claim 1 , further comprising:
processing the user communications to generate a unique voice signature associated with the user; and
using the unique voice signature to automatically identify and remove the user communications from the recording.
7. The computer-implemented method of claim 1 , further comprising:
activating an agent bot, wherein the agent bot is implemented to solicit the affirmative user consent; and
receiving the affirmative user consent, wherein the affirmative user consent is provided in a response to a solicitation generated by the agent bot during the communications session.
8. A system, comprising:
one or more processors; and
memory storing thereon instructions that, as a result of being executed by the one or more processors, cause the system to:
dynamically process, in real-time, communications exchanged during a communications session between a user and an agent to isolate user communications associated with the user, wherein the communications session is associated with an intent;
continuously generate a recording, wherein the recording includes the user communications and agent communications associated with the agent, and wherein the recording is generated according to an affirmative user consent;
detect a revocation of the affirmative user consent during the communications session, wherein the revocation is communicated through a new user communication exchanged during the communications session;
automatically remove the user communications from the recording such that the recording is devoid of the user communications and any subsequent user communications exchanged during the communications session;
dynamically train a machine learning algorithm to generate a set of inferences corresponding to user sentiment associated with the intent, wherein the machine learning algorithm is dynamically trained using historic recordings corresponding to historic communications sessions between users and agents, and feedback corresponding to the historic communications sessions;
process the agent communications from the recording through the machine learning algorithm to generate the set of inferences; and
generate agent analytics corresponding to the intent, wherein the agent analytics are generated based on the set of inferences and the recording.
9. The system of claim 8 , wherein the instructions that cause the system to automatically remove the user communications from the recording further cause the system to:
insert one or more audial nulls in the recording to replace the user communications.
10. The system of claim 8 , wherein the instructions that cause the system to generate the agent analytics further cause the system to:
identify a set of agent training needs, wherein the set of agent training needs correspond to actions performable to improve agent responses to intents.
11. The system of claim 8 , wherein the instructions that cause the system to detect the revocation of the affirmative user consent further cause the system to:
process the new user communication as the new user communication is exchanged during the communications session; and
detect one or more anchor terms corresponding to a request to cease recording of the user communications.
12. The system of claim 8 , wherein the instructions further cause the system to:
calculate a voice signature associated with the agent, wherein the voice signature is calculated during an onboarding process; and
identify the user communications based on the user communications not corresponding to the voice signature.
13. The system of claim 8 , wherein the instructions further cause the system to:
process the user communications to generate a unique voice signature associated with the user; and
use the unique voice signature to automatically identify and remove the user communications from the recording.
14. The system of claim 8 , wherein the instructions further cause the system to:
activate an agent bot, wherein the agent bot is implemented to solicit the affirmative user consent; and
receive the affirmative user consent, wherein the affirmative user consent is provided in a response to a solicitation generated by the agent bot during the communications session.
15. A non-transitory computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to:
dynamically process, in real-time, communications exchanged during a communications session between a user and an agent to isolate user communications associated with the user, wherein the communications session is associated with an intent;
continuously generate a recording, wherein the recording includes the user communications and agent communications associated with the agent, and wherein the recording is generated according to an affirmative user consent;
detect a revocation of the affirmative user consent during the communications session, wherein the revocation is communicated through a new user communication exchanged during the communications session;
automatically remove the user communications from the recording such that the recording is devoid of the user communications and any subsequent user communications exchanged during the communications session;
dynamically train a machine learning algorithm to generate a set of inferences corresponding to user sentiment associated with the intent, wherein the machine learning algorithm is dynamically trained using historic recordings corresponding to historic communications sessions between users and agents, and feedback corresponding to the historic communications sessions;
process the agent communications from the recording through the machine learning algorithm to generate the set of inferences; and
generate agent analytics corresponding to the intent, wherein the agent analytics are generated based on the set of inferences and the recording.
16. The non-transitory computer-readable storage medium of claim 15 , wherein the executable instructions that cause the computer system to automatically remove the user communications from the recording further cause the computer system to:
insert one or more audial nulls in the recording to replace the user communications.
17. The non-transitory computer-readable storage medium of claim 15 , wherein the executable instructions that cause the computer system to generate the agent analytics further cause the computer system to:
identify a set of agent training needs, wherein the set of agent training needs correspond to actions performable to improve agent responses to intents.
18. The non-transitory computer-readable storage medium of claim 15 , wherein the executable instructions that cause the computer system to detect the revocation of the affirmative user consent further cause the computer system to:
process the new user communication as the new user communication is exchanged during the communications session; and
detect one or more anchor terms corresponding to a request to cease recording of the user communications.
19. The non-transitory computer-readable storage medium of claim 15 , wherein the executable instructions further cause the computer system to:
calculate a voice signature associated with the agent, wherein the voice signature is calculated during an onboarding process; and
identify the user communications based on the user communications not corresponding to the voice signature.
20. The non-transitory computer-readable storage medium of claim 15 , wherein the executable instructions further cause the computer system to:
process the user communications to generate a unique voice signature associated with the user; and
use the unique voice signature to automatically identify and remove the user communications from the recording.
21. The non-transitory computer-readable storage medium of claim 15 , wherein the executable instructions further cause the computer system to:
activate an agent bot, wherein the agent bot is implemented to solicit the affirmative user consent; and
receive the affirmative user consent, wherein the affirmative user consent is provided in a response to a solicitation generated by the agent bot during the communications session.