Back office services of an intelligent automated agent for a contact center

• US 9,648,167 B2
• Filed: 05/05/2014
• Issued: 05/09/2017
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Genesys Cloud Services Incorporated
• Original Assignee: Genesys Telecommunications Laboratories Incorporated (Genesys Cloud Services Incorporated)
• Inventors: Riahi, Akbar, Ristock, Herbert Willi Artur
• Primary Examiner(s): Asanbayev, Oleg
• Application Number:
  US14/270,342
• Publication Number:
  US 20140270146A1
• Time in Patent Office: 1,100 Days
• Field of Search: 37926501-26514, 37926601-2661
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04M 2203/401 Performance feedback
• CPC Class Codes: H04M 3/00 Automatic or semi-automatic exchanges
• CPC Class Codes: H04M 3/4936 Speech interaction details speech recognition per se G10L15/00
• 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 3/5235 Dependent on call type or called number [DNIS]
• CPC Class Codes: H04M 5/00 Manual exchanges substation equipment in general H04M1/00

Abstract

A back office services of an intelligent automated agent for a contact center is provided. The back office services is configured to run on a processor coupled to a non-transitory storage device. The back office services includes: a customer profile module configured to access a profile of a customer from a customer profile database stored on the storage device, the profile of the customer including interaction data from interactions involving the customer and the contact center, and analysis results from analyzing the interaction data between the interactions involving the customer and the contact center; and a content analysis module configured to generate new analysis results by performing the analyzing of the interaction data between consecutive interactions of the interactions involving the customer and the contact center, and update the analysis results of the profile of the customer on the storage device to reflect the new analysis results.

Claims

1. A method for providing back office services for a contact center to a customer through an intelligent automated agent, the method comprising:

running the intelligent automated agent on a processor coupled to a non-transitory storage device;

accessing a profile of the customer from a customer profile database stored on the storage device, the profile of the customer comprising interaction data from interactions involving the customer and the contact center, and analysis results from analyzing the interaction data between the interactions involving the customer and the contact center, wherein the analysis results comprises a list of pending transactions and/or requests by the customer that are not yet completed;

generating new analysis results by performing the analyzing of the interaction data between consecutive interactions of the interactions involving the customer and the contact center;

classifying customers of the contact center into different classifications based on their corresponding analysis results of the profiles of the customers;

generating corresponding new analysis results by performing the analyzing of respective interaction data of the profiles of the customers using different analysis criteria for the different classifications;

updating the analysis results of the profile of the customer on the storage device to reflect the new analysis results;

re-accessing the profile of the customer during a next interaction of the interactions involving the customer and the contact center;

determining, based on the re-accessed profile of the customer, whether the next interaction is to be handled by the automated agent or a live agent, wherein the determining includes determining, based on the profile of the customer, as to whether there are cross-sale or up-sale opportunities;

detecting customer mood;

selecting the live agent amongst a plurality of agents based on the detected customer mood;

forwarding the next interaction to the live agent instead of the automated agent in response to determining that cross-sale or up-sale opportunities exist;

in response to the determining that the next interaction is to be handled by the automated agent;

adjusting a behavior of the automated agent during the next interaction by factoring in the analysis results of the re-accessed profile of the customer, wherein the adjusting of the behavior includes deleting or altering an output of the automated agent based on the analysis results of the re-accessed profile of the customer; and

updating the interaction data of the re-accessed profile on the storage device to reflect the next interaction; and

addressing the pending transactions and/or requests during future interactions of the interactions involving the customer and the contact center.

2. The method of claim 1, wherein

the analysis results comprise actions to be taken by the automated agent during future interactions of the interactions involving the customer and the contact center, and

the method further comprises performing the actions by the automated agent during the future interactions.

3. The method of claim 1, further comprising:

generating additional analysis results between the consecutive interactions by re-analyzing the interaction data using newer analysis criteria since the updating of the analysis results of the profile of the customer to reflect the new analysis results; and

updating the analysis results of the profile of the customer on the storage device to reflect the additional analysis results.

4. The method of claim 1, further comprising assigning an appropriate live agent from a pool of live agents to the customer based on the analysis results of the profile of the customer.

5. The method of claim 1, further comprising deleting or altering suggested responses to the customer based on the analysis results of the profile of the customer.

11. The method of claim 1 further comprising selecting the live agent amongst a plurality of agents based on a search of agents with skills for handling both a primary need of the customer, and the cross-sale or up-sale to the customer.

12. The method of claim 11 further comprising selecting the live agent amongst the plurality of agents based on a search of agents who fit the profile of the customer.

6. A system for a contact center 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;

access a profile of the customer from a customer profile database stored on the storage device, the profile of the customer comprising interaction data from interactions involving the customer and the contact center, and analysis results from analyzing the interaction data between the interactions involving the customer and the contact center, wherein the analysis results comprises a list of pending transactions and/or requests by the customer that are not yet completed;

generate new analysis results by performing the analyzing of the interaction data between consecutive interactions of the interactions involving the customer and the contact center;

classify customers of the contact center into different classifications based on their corresponding analysis results of the profiles of the customers;

generate corresponding new analysis results by performing the analyzing of respective interaction data of the profiles of the customers using different analysis criteria for the different classifications;

update the analysis results of the profile of the customer on the storage device to reflect the new analysis results;

re-access the profile of the customer during a next interaction of the interactions involving the customer and the contact center;

determine, based on the profile of the customer, whether the next interaction is to be handled by an automated agent or a live agent, wherein the instructions that cause the processor to determine include instructions that cause the processor to determine, based on the profile of the customer, as to whether there are cross-sale or up-sale opportunities;

detect customer mood;

select the live agent amongst a plurality of agents based on the detected customer mood;

forward the next interaction to the live agent instead of the automated agent in response to determining that cross-sale or up-sale opportunities exist;

in response to the determining that the next interaction is to be handled by the automated agent;

adjust a behavior of the automated agent during the next interaction by factoring in the analysis results of the re-accessed profile of the customer, wherein the adjusting of the behavior includes deleting or altering an output of the automated agent based on the analysis results of the re-accessed profile of the customer; and

update the interaction data of the re-accessed profile on the storage device to reflect the next interaction; and

address the pending transactions and/or requests during future interactions of the interactions involving the customer and the contact center.

7. The system of claim 6, wherein

the analysis results comprise actions to be taken by the automated agent during future interactions of the interactions involving the customer and the contact center, and

the instructions, when executed by the processor, further cause the processor to perform the actions during the future interactions.

8. The system of claim 6, wherein the instructions, when executed by the processor, further cause the processor to:

generate additional analysis results between the consecutive interactions by re-analyzing the interaction data using newer analysis criteria since the updating of the analysis results of the profile of the customer to reflect the new analysis results; and

update the analysis results of the profile of the customer on the storage device to reflect the additional analysis results.

9. The system of claim 6, wherein the instructions, when executed by the processor, further cause the processor to:

classify customers of the contact center into different classifications based on their corresponding analysis results of the profiles of the customers; and

generate corresponding new analysis results by performing the analyzing of respective interaction data of the profiles of the customers using different analysis criteria for the different classifications.

10. The system of claim 6, wherein

the analysis results comprises a list of pending transactions and/or requests by the customer that are not yet completed, and

the instructions, when executed by the processor, further cause the processor to address the pending transactions and/or requests during future interactions of the interactions involving the customer and the contact center.