Automated redistribution of queries to underutilized channels

1. A computing platform, comprising:

at least one processor; and

memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

monitor, via a computing device, user traffic for one or more customer service communication channels;

identify, for the one or more customer service communication channels and based on the user traffic, estimated waft times for a plurality of users to be served via the one or more customer service communication channels;

initiate, via an intelligent virtual assistant, a communication with a given user of the plurality of users via a first customer service communication channel of the one or more customer service communication channels;

receive, via the intelligent virtual assistant and based on the communication with the given user via the first customer service communication channel, one or more attributes of a query of the given user;

train a machine learning model to detect patterns of estimated wait times and attributes of queries;

identify, from one or more external data sources, an event that may impact the estimated wait times;

train the machine learning model to determine an allocation of resources for the one or more customer service communication channels;

determine, based on the identified event and by applying the machine learning model, the allocation of resources for the one or more customer service communication channels;

select, via the computing device by applying the machine learning model and based on the estimated wait times, the one or more attributes of the query of the given user and the allocation of resource for the one or more customer service communication channels, a second customer service communication channel of the one or more customer service communication channels different from the first customer service communication channel;

provide, via the intelligent virtual assistant and to an enterprise agent associated with the second customer service communication channel, the one or more attributes of the query of the given user received based on the communication with the given user via the first customer service communication channel; and

direct the given user to the second customer service communication channel.

2. The computing platform of claim 1 , wherein the one or more customer service communication channels comprise one of: a telephone communication channel, a web interface, a video teleconference interface, an electronic mail communication channel, and the intelligent virtual assistant.

3. The computing platform of claim 1 , wherein the instructions to direct the given user to the second customer service communication channel comprise additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

address the query via the intelligent virtual assistant.

4. The computing platform of claim 1 , wherein the instructions to select the second customer service communication channel comprise additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

determine whether a licensed professional is needed to address the query; and

upon a determination that a licensed professional is needed to address the query, select the second customer service communication channel associated with the licensed professional.

5. The computing platform of claim 1 , wherein the instructions to select the second customer service communication channel comprise additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

identify, based on the one or more attributes of the query of the given user and the estimated wait times, a geographic region; and

select the second customer service communication channel based on the identified geographic region.

6. The computing platform of claim 1 , wherein the instructions comprise additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to: train the machine learning model to select the second customer service communication channel.

7. The computing platform of claim 6 , wherein the instructions comprise additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

apply the trained machine learning model to select the second customer service communication channel.

8. The computing platform of claim 1 , wherein the instructions comprise additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

determine that the given user has access to a higher generation wireless communication interface; and

recommend, to the given user and to address the query, a video teleconference interface based on the higher generation wireless communication interface.

9. The computing platform of claim 1 , wherein the instructions comprise additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

determine, based on location data from a higher generation wireless communication interface, a physical location of the given user; and

recommend, to the given user and based on the physical location, a physical facility to address the query.

10. A method, comprising:

at a computing platform comprising at least one processor, and memory:

identifying, via a computing device and for one or more customer service communication channels, estimated wait times for a plurality of users to be served via the one or more customer service communication channels;

initiating, via an intelligent virtual assistant, a communication with a given user of the plurality of users via a first customer service communication channel of the one or more customer service communication channels;

receiving, via the intelligent virtual assistant and based on the communication with the given user via the first customer service communication channel, one or more attributes of a query of the given user;

training a machine learning model to detect patterns of estimated wait times and attributes of queries;

identifying, from one or more external data sources, an event that may impact the estimated wait times;

training the machine learning model to determine an allocation of resources for the one or more customer service communication channels;

determining, based on the identified event and by applying the machine learning model, the allocation of resources for the one or more customer service communication channels;

selecting, by applying the machine learning model and based on the one or more attributes of the query of the given user and the allocation of resources, a second customer service communication channel of the one or more customer service communication channels different from the first customer service communication channel;

providing, via the intelligent virtual assistant and to an enterprise agent associated with the second customer service communication channel, the one or more attributes of the query of the given user received based on the communication with the given user via the first customer service communication channel; and

directing the given user to the second customer service communication channel.

11. The method of claim 10 , wherein the one or more customer service communication channels comprise one of: a telephone communication channel, a web interface, a video teleconference interface, an electronic mail communication channel, and the intelligent virtual assistant.

12. The method of claim 10 , further comprising:

addressing the query via the intelligent virtual assistant.

13. The method of claim 10 , further comprising:

determining whether a licensed professional is needed to address the query; and

upon a determination that a licensed professional is needed to address the query, selecting the second customer service communication channel associated with the licensed professional.

14. The method of claim 10 , further comprising:

identifying, based on the one or more attributes of the query of the given user and the estimated wait times, a geographic region; and

selecting the second customer service communication channel based on the identified geographic region.

15. The method of claim 10 , further comprising:

determining that the given user has access to a higher generation wireless communication interface; and

recommending, to the given user and to address the query, a video teleconference interface based on the higher generation wireless communication interface.

16. One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, at least one physical sensor communicatively coupled to the at least one processor, and memory, cause the computing platform to:

identify, for one or more customer service communication channels, estimated wait times for a plurality of users to be served via the one or more customer service communication channels;

initiate, via an intelligent virtual assistant, a communication with a given user of the plurality of users via a first customer service communication channel of the one or more customer service communication channels;

receive, via the intelligent virtual assistant and based on the communication with the given user via the first customer service communication channel, one or more attributes of a query of the given user;

train a machine learning model to detect patterns of estimated wait times and attributes of queries;

identify, from one or more external data sources, an event that may impact the estimated wait times;

train the machine learning model to determine an allocation of resources for the one or more customer service communication channels;

determine, based on the identified event and by applying the machine learning model, the allocation of resources for the one or more customer service communication channels;

select, via the computing platform by applying the machine learning model and based on the estimated wait times, the one or more attributes of the query of the given user and the allocation of resources, a second customer service communication channel of the one or more customer service communication channels different from the first customer service communication channel;

provide, via the intelligent virtual assistant and to an enterprise agent associated with the second customer service communication channel, the one or more attributes of the query of the given user; and

direct the given user to the second customer service communication channel.