Federated intelligent contact center concierge service
Customers often call a contact center to resolve an issue only to find the contact center cannot resolve the customer's issue and instead requires a third party to perform some action. By monitoring a customer's communication with an agent, an automated process may generate a workflow to address the issue comprising at least one action to be performed by a third party. The third party is then contacted, in real-time or offline, and provided with their actions to be performed. Records are written to a blockchain describing authentications, actions to take and by whom, and the completion of such actions. The resulting success, or lack thereof, is provided as feedback to further refine the accuracy of the automatic determinations of the workflow and/or the identity of the particular third parties.
1. A system, comprising:
a server;
a network interface to a network; and
wherein at least one processor of the server performs:
connecting, via the network, to a customer communication device for a communication comprising an audio portion comprising speech provided by a customer utilizing the customer communication device and wherein the communication is a real-time communication;
analyzing the speech to identify a work item;
upon determining the work item requires an action from a third party, analyzing the speech to identify the third party;
constructing a workflow comprising a number of steps that, when each step has been completed, resolves the work item;
providing at least one third-party step of the number of steps to the third party that, when complete, performs the action; and
performing at least one host step of the number of steps.
2. The system of claim 1 , wherein analyzing the speech to identify the work item comprises providing the speech to a neural network trained to identify work items and receiving the work item therefrom.
3. The system of claim 2 , wherein the neural network is trained, comprising at least one processor executing a computer-implemented method of training a neural network for work item identification comprising:
collecting a set of work items from a database;
applying one or more transformations to each work item including substituting a word with a synonymous word, substituting a word with a synonymous phrase, substituting a purpose for a topic associated with the purpose, substituting the topic associated with the purpose of the communication with the purpose, inserting at least one redundant word, removing at least one redundant word, removing a first unique topic, and adding a second unique topic to create a modified set of work items;
creating a first training set comprising the collected set of work items, the modified set of work items, and a set of customer provided content absent work items;
training the neural network in a first stage of training using the first training set;
creating a second training set for a second stage of training comprising the first training set and customer provided content absent work items that are incorrectly detected as comprising a work item after the first stage of training; and
training the neural network in the second stage of training using the second training set.
4. The system of claim 1 , wherein analyzing the speech to identify the third party comprises providing the speech to a neural network trained to identify third parties and receiving the third party therefrom.
5. The system of claim 4 , wherein the neural network is trained, comprising at least one processor executing a computer-implemented method of training a neural network for work item identification comprising:
collecting a set of third-party actions from a database;
applying one or more transformations to a third-party action including substituting a third-party service for a third-party name, substituting a third-party name for a third-party service, substituting a third-party action for a third-party name, substituting a third-party name for a third-party action, substituting a work item topic for a third-party name, and substituting a third-party name for a work item subject to create a modified set of work items;
creating a first training set comprising the collected set of third-party actions, the modified set of work items, and a set of communication content absent a third-party action;
training the neural network in a first stage of training using the first training set;
creating a second training set for a second stage of training comprising the first training set and host actions that are incorrectly determined as third-party actions after the first stage of training; and
training the neural network in the second stage of training using the second training set.
6. The system of claim 1 , wherein the communication includes an automated agent engaging in the communication with the customer.
7. The system of claim 1 , wherein the communication includes an agent communication device utilized by an agent to engage in the communication with the customer.
8. The system of claim 1 , wherein the action is encoded as encrypted blocks and added to a blockchain.
9. The system of claim 8 , wherein at least one of the encrypted blocks comprises a self-executing smart contract in response to determining an corresponding action has been completed.
10. The system of claim 1 , wherein upon determining the work item requires the action from the third party, joining a third-party communication device to the communication and conducting a portion of the communication therewith.
11. A method, comprising:
connecting, via a network, to a customer communication device for a communication comprising an audio portion comprising speech provided by a customer utilizing the customer communication device and wherein the communication is a real-time communication;
analyzing the speech to identify a work item;
upon determining the work item requires an action from a third party, analyzing the speech to identify the third party;
constructing a workflow comprising a number of steps that, when each step has been completed, resolves the work item; and
providing at least one third-party step of the number of steps to the third party that, when complete, performs the action.
12. The method of claim 11 , wherein analyzing the speech to identify the work item comprises providing the speech to a neural network trained to identify work items and receiving the work item therefrom.
13. The method of claim 12 , wherein the neural network is trained, comprising at least one processor executing a computer-implemented method of training a neural network for work item identification comprising:
collecting a set of work items from a database;
applying one or more transformations to each work item including substituting a word with a synonymous word, substituting a word with a synonymous phrase, substituting a purpose for a topic associated with the purpose, substituting the topic associated with the purpose of the communication with the purpose, inserting at least one redundant word, removing at least one redundant word, removing a first unique topic, and adding a second unique topic to create a modified set of work items;
creating a first training set comprising the collected set of work items, the modified set of work items, and a set of customer provided content absent work items;
training the neural network in a first stage of training using the first training set;
creating a second training set for a second stage of training comprising the first training set and customer provided content absent work items that are incorrectly detected as comprising a work item after the first stage of training; and
training the neural network in the second stage of training using the second training set.
14. The method of claim 11 , wherein analyzing the speech to identify the third party comprises providing the speech to a neural network trained to identify third parties and receiving the third party therefrom.
15. The method of claim 14 , wherein the neural network is trained, comprising at least one processor executing a computer-implemented method of training a neural network for work item identification comprising:
collecting a set of third-party actions from a database;
applying one or more transformations to a third-party action including substituting a third-party service for a third-party name, substituting a third-party name for a third-party service, substituting a third-party action for a third-party name, substituting a third-party name for a third-party action, substituting a work item topic for a third-party name, and substituting a third-party name for a work item subject to create a modified set of work items;
creating a first training set comprising the collected set of third-party actions, the modified set of work items, and a set of communication content absent a third-party action;
training the neural network in a first stage of training using the first training set;
creating a second training set for a second stage of training comprising the first training set and host actions that are incorrectly determined as third-party actions after the first stage of training; and
training the neural network in the second stage of training using the second training set.
16. The method of claim 11 , wherein the communication includes an automated agent engaging in the communication with the customer.
17. The method of claim 11 , wherein the communication includes an agent communication device utilized by an agent to engage in the communication with the customer.
18. The method of claim 11 , wherein the action is encoded as encrypted blocks and added to a blockchain.
19. The method of claim 11 , wherein upon determining the work item requires the action from the third party, joining a third-party communication device to the communication and conducting a portion of the communication therewith.
20. A system, comprising:
means to connect a customer communication device for a communication comprising an audio portion comprising speech provided by a customer utilizing the customer communication device and wherein the communication is a real-time communication;
means to analyze the speech to identify a work item;
means to, upon determining the work item requires an action from a third party, analyze the speech to identify the third party;
means to construct a workflow comprising a number of steps that, when each step has been completed, resolves the work item; and
means to provide at least one third-party step of the number of steps to the third party that, when complete, performs the action.