INTELLIGENT AUTOMATED AGENT FOR A CONTACT CENTER

• US 20140314225A1
• Filed: 04/19/2013
• Published: 10/23/2014
• Est. Priority Date: 03/15/2013
• Status: Abandoned Application

• Current Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Original Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Inventors: Riahi, Akbar, Ristock, Herbert Willi Artur
• Application Number:
  US13/866,763
• Publication Number:
  US 20140314225A1
• Time in Patent Office: Days
• US Class Current: 379/265.09
• CPC Class Codes: G06Q 30/01 Customer relationship services
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04L 51/02 using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
• CPC Class Codes: H04L 51/04 Real-time or near real-time messaging, e.g. instant messaging [IM]
• CPC Class Codes: H04M 2203/401 Performance feedback
• CPC Class Codes: H04M 2203/551 Call history
• CPC Class Codes: H04M 3/5166 in combination with interactive voice response systems or voice portals, e.g. as front-ends
• CPC Class Codes: H04M 3/5175 Call or contact centers supervision arrangements
• CPC Class Codes: H04M 3/5183 Call or contact centers with computer-telephony arrangements
• CPC Class Codes: H04M 3/5191 interacting with the Internet
• CPC Class Codes: H04M 3/5235 Dependent on call type or called number [DNIS]

Abstract

A system for handling customer interactions with a contact center for an enterprise includes an intelligent automated agent that includes a processor, a non-transitory storage device configured to store customer profile data, and a memory. The memory has instructions stored thereon that, when executed by the processor, causes the processor to: run an artificial intelligence engine configured to learn knowledge about a customer from past interactions between the contact center and the customer, and to apply the learned knowledge to future interactions; and maintain the customer profile data on the storage device. The maintaining of the customer profile data includes retrieving the customer profile data at a beginning of a new interaction, using the retrieved customer profile data to decide how to handle the new interaction, and updating the customer profile data after completion of the new interaction to reflect the new interaction as one of the past interactions.

Claims

1. A system for handling customer interactions with a contact center for an enterprise, the system comprising:

an intelligent automated agent comprising;

a processor;

a non-transitory storage device configured to store customer profile data; and

a memory, wherein the memory has instructions stored thereon that, when executed by the processor, causes the processor to;

run an artificial intelligence engine configured to learn knowledge about a customer from past ones of the customer interactions between the contact center and the customer, and to apply the learned knowledge to future ones of the customer interactions between the contact center and the customer; and

maintain the customer profile data on the storage device, comprising;

retrieving the customer profile data for the customer at a beginning of a new one of the customer interactions between the contact center and the customer;

using the retrieved customer profile data to decide how to handle the new one of the customer interactions; and

updating the customer profile data for the customer on the storage device after completion of the new one of the customer interactions to reflect the new one of the customer interactions as one of the past ones of the customer interactions between the contact center and the customer.

2. The system of claim 1, wherein the enterprise comprises a plurality of enterprises.

3. The system of claim 2, wherein the automated agent comprises a corresponding plurality of automated agents.

4. The system of claim 1, wherein the artificial intelligence engine comprises a Petri net or neural network configured to build connections over time from learned behavior.

5. The system of claim 1, wherein the artificial intelligence engine is further configured to learn from classification.

6. The system of claim 1, wherein the artificial intelligence engine is further configured to learn from numerical regression.

7. The system of claim 1, wherein the learned knowledge comprises learned voice characteristics of the customer.

8. The system of claim 7, wherein the artificial intelligence engine is further configured to apply the learned voice characteristics of the customer to identify the customer in the future ones of the customer interactions between the contact center and the customer.

9. The system of claim 7, wherein the artificial intelligence engine is further configured to apply the learned voice characteristics of the customer to verify an identity of the customer in the future ones of the customer interactions between the contact center and the customer.

10. The system of claim 1, wherein the customer interactions comprise real time interactions.

11. The system of claim 10, wherein the real time interactions comprise telephone calls, live chats, instant messaging, text messaging, video conferences, multi-media interactions, and/or web interactions.

12. The system of claim 1, wherein the customer interactions comprise non-real time interactions.

13. The system of claim 12, wherein the non-real time interactions comprise e-mail exchanges.

14. A method of handling customer interactions with a contact center for an enterprise by an intelligent automated agent, the method comprising:

learning, by the automated agent using an artificial intelligence engine running on a processor, knowledge from past ones of the customer interactions between the contact center and a customer, and applying the learned knowledge to future ones of the customer interactions between the contact center and the customer; and

maintaining customer profile data by the processor on a non-transitory storage device, the maintaining of the customer profile data being performed by the automated agent running on the processor and comprising;

retrieving the customer profile data for the customer at a beginning of a new one of the customer interactions between the contact center and the customer;

using the retrieved customer profile data to decide how to handle the new one of the customer interactions; and

updating the customer profile data for the customer on the storage device after completion of the new one of the customer interactions to reflect the new one of the customer interactions as one of the past ones of the customer interactions between the contact center and the customer.

15. The method of claim 14, wherein the artificial intelligence engine comprises a Petri net or neural network configured to build connections over time from learned behavior.

16. The method of claim 14, wherein the retrieving of the customer profile data is in real time during the new one of the customer interactions when the new one of the customer interactions is a real-time interaction.

17. The method of claim 16, wherein the real-time interaction comprises a telephone call, a live chat, an instant messaging session, a text messaging session, a video conference, a multi-media interaction, and/or a web interaction.

18. The method of claim 14, wherein the updating of the customer profile data is in non-real time after the completion of the new one of the customer interactions.

19. The method of claim 14, wherein

the learned knowledge comprises learned voice characteristics of the customer, and

the method further comprises applying, by the artificial intelligence engine, the learned voice characteristics of the customer to identify the customer in the future ones of the customer interactions between the contact center and the customer.

20. The method of claim 14, wherein the learned knowledge comprises learned voice characteristics of the customer, and

the method further comprises applying, by the artificial intelligence engine, the learned voice characteristics of the customer to verify an identity of the customer in the future ones of the customer interactions between the contact center and the customer.