Machine Assisted Troubleshooting of a Customer Support Issue

• US 20140279718A1
• Filed: 03/12/2013
• Published: 09/18/2014
• Est. Priority Date: 03/12/2013
• Status: Abandoned Application

• Current Assignee: Conduent Business Services, LLC (Conduent, Inc.)
• Original Assignee: Xerox Business Services, LLC (Conduent, Inc.)
• Inventors: Southey, Edward Charles, Forsyth, Timothy John, Piper, Mark, Butt, David John, Wallingford, Paul Martin, Griffin, Daniel James, McKinley, Jeremy J., Hooper, Benjamin James, Thelin, Michael Carl, Gyles, Nicholas Mark, Joyce, Timothy T.
• Application Number:
  US13/795,087
• Publication Number:
  US 20140279718A1
• Time in Patent Office: Days
• US Class Current: 706/11
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models

Abstract

A knowledge interface is provided that interacts with a user to identify a solution to a customer problem or issue with respect to a particular product or service. The knowledge interface includes data processing functionality configured to dynamically generate a number of components that are presented in at least one display window for display to the user. The components include first data identifying a set of predetermined symptoms linked to the problem or issue and related interface elements for classification of the set of predetermined symptoms, second data identifying a set of predetermined root causes linked to the set of predetermined symptoms and related interface elements for classification of the set of predetermined root causes, and third data identifying a set of solutions linked to the set of predetermined root causes. The third data identifies a best solution based upon the predetermined root causes and their associated class designations.

Claims

1. A knowledge interface that interacts with a user-operated data processing system via networked communication to identify a solution to problem or issue experienced by a customer with respect to a particular product or service, the knowledge interface comprising:

data processing functionality that supplies information to the user-operated data processing system, the information representing a number of components that are presented in at least one display window displayed by the user-operated data processing system, wherein the components include

i) first data identifying a set of predetermined symptoms linked to the problem or issue experienced by the customer,

ii) first interface elements that are configured to allow the user to classify the set of predetermined symptoms of i) into two classes including a first class of symptoms representing symptoms most likely experienced by the customer and a second class of symptoms representing symptoms most likely not experienced by the customer,

iii) second data identifying a set of predetermined root causes linked to the set of predetermined symptoms of i),

iv) second interface elements that are configured to allow the user to classify the set of predetermined root causes of iii) into two classes including a first class of root causes representing root causes most likely experienced by the customer and a second class of root causes representing root causes most likely not experienced by the customer, and

v) third data identifying a set of solutions linked to the set of predetermined root causes of iii), wherein the third data identifies a best solution based upon the predetermined root causes of iii) and their associated class designations as dictated by user input with the second interface elements.

2. A knowledge interface according to claim 1, further comprising:

a user input mechanism that is configured to enable the user to specify a natural text description of at least one symptom of the problem or issue experienced by the customer with respect to a particular product or service; and

an interface to an analysis engine that is configured to identify the set of predetermined symptoms, wherein the set of predetermined symptoms are linked by statistical analysis to the natural text description specified by user operation of the user input mechanism.

3. A knowledge interface according to claim 2, wherein:

the statistical analysis implements a naive Bayes classification methodology.

4. A knowledge interface according to claim 2, wherein:

the statistical analysis associates a confidence level with the link between a given predetermined symptom and the natural language textual description of the problem or issue experienced by the customer with respect to a particular product or service.

5. A knowledge interface according to claim 4, wherein:

confidence levels associated with the set of predetermined symptoms are used by the knowledge interface to order display of the set of predetermined symptoms in the at least one display window.

6. A knowledge interface according to claim 1, wherein:

context that identifies the particular product or service is supplied to the knowledge interface.

7. A knowledge interface according to claim 6, wherein:

the context is derived from interaction between a call center representative and the customer.

8. A knowledge interface according to claim 6, wherein:

the context is supplied by input from the customer.

9. A knowledge interface according to claim 1, wherein:

the components further include a user input mechanism to select a best solution and trigger the display of additional information regarding the best solution to the user.

10. A knowledge interface according to claim 9, wherein:

the additional information is selected from the group including

i) a document or other web content,

ii) an external link,

iii) an OTA flow for mobile device configuration and programming,

iv) device attributes, and

v) a simulation that guides the call center representative through steps to fix a particular problem or issue.

11. A knowledge interface according to claim 9, wherein:

the components include a user input mechanism to indicate whether or not the best solution was successful in solving the problem or issue.

12. A knowledge interface according to claim 1, further comprising:

a database that stores collected data derived from interaction with the user and associated with the problem or issue.

13. A knowledge interface according to claim 12, wherein:

the collected data is used to train the analysis engine for subsequent operations.

14. A knowledge interface according to claim 1, wherein:

the user of the knowledge interface is a call center representative.

15. A knowledge interface according to claim 1, wherein:

the user of the knowledge interface is the customer.

16. A knowledge interface according to claim 1, wherein:

the first data, the second data and the third data are displayed in a plurality of distinct regions of a display window, wherein the plurality of regions are laid out adjacent one another across the horizontal extent of the display window.

17. A knowledge interface according to claim 16, wherein:

the plurality of regions include a region that displays the first data and second data after being classified in accordance with user input.

18. A method for identifying a solution to problem or issue experienced by a customer with respect to a particular product or service, the method comprising:

supplying information to a user-operated data processing system via networked communication, the information representing a number of components that are presented in at least one display window displayed by the user-operated data processing system, wherein the components include

i) first data identifying a set of predetermined symptoms linked to the problem or issue experienced by the customer,

ii) first interface elements that are configured to allow the user to classify the set of predetermined symptoms of i) into two classes including a first class of symptoms representing symptoms most likely experienced by the customer and a second class of symptoms representing symptoms most likely not experienced by the customer,

iii) second data identifying a set of predetermined root causes linked to the set of predetermined symptoms of i),

iv) second interface elements that are configured to allow the user to classify the set of predetermined root causes of iii) into two classes including a first class of root causes representing root causes most likely experienced by the customer and a second class of root causes representing root causes most likely not experienced by the customer, and

v) third data identifying a set of solutions linked to the set of predetermined root causes of iii), wherein the third data identifies a best solution based upon the predetermined root causes of iii) and their associated class designations as dictated by user input with the second interface elements.

19. A method according to claim 18, further comprising:

interacting with the user to enable the user to specify a natural text description of at least one symptom of the problem or issue experienced by the customer with respect to a particular product or service; and

interfacing to an analysis engine that is configured to identify the set of predetermined symptoms, wherein the set of predetermined symptoms are linked by statistical analysis to the natural text description specified by user operation of the user input mechanism.

20. A method according to claim 19, wherein:

the statistical analysis implements a naive Bayes classification methodology.

21. A method according to claim 19, wherein:

the statistical analysis associates a confidence level with the link between a given predetermined symptom and the natural language textual description of the problem or issue experienced by the customer with respect to a particular product or service.

22. A method according to claim 21, wherein:

utilizing the confidence levels associated with the set of predetermined symptoms to order display of the set of predetermined symptoms in the at least one display window.

23. A method according to claim 18, further comprising:

deriving context that identifies the particular product or service.

24. A method according to claim 23, wherein:

the context is derived from interaction between a call center representative and the customer.

25. A method according to claim 23, wherein:

the context is supplied by input from the customer.

26. A method according to claim 18, further comprising:

interacting with the user to select a best solution and triggering the display of additional information regarding the best solution to the user.

27. A method according to claim 26, wherein:

the additional information is selected from the group including

i) a document or other web content,

ii) an external link,

iii) an OTA flow for mobile device configuration and programming,

iv) device attributes, and

v) a simulation that guides the call center representative through steps to fix a particular problem or issue.

28. A method according to claim 26, further comprising:

interacting with the user to indicate whether or not the best solution was successful in solving the problem or issue.

29. A method according to claim 18, further comprising:

storing in a database collected data derived from interaction with the user and associated with the problem or issue.

30. A method according to claim 29, further comprising:

using the collected data to train the analysis engine for subsequent operations.

31. A method according to claim 18, wherein:

the user of the knowledge interface is a call center representative.

32. A method according to claim 18, wherein:

the user of the knowledge interface is the customer.

33. A method according to claim 18, wherein:

the first data, the second data and the third data are displayed in a plurality of distinct regions of a display window, wherein the plurality of regions are laid out adjacent one another across the horizontal extent of the display window.

34. A method according to claim 33, wherein:

the plurality of regions include a region that displays the first data and second data after being classified in accordance with user input.

35. A knowledge interface that interacts with a user to identify a solution to problem or issue experienced by a customer with respect to a particular product or service, the knowledge interface comprising:

data processing functionality that presents a number of components in at least one display window displayed to the user, wherein the components include

i) first data identifying a set of predetermined symptoms linked to the problem or issue experienced by the customer,

ii) first interface elements that are configured to allow the user to classify the set of predetermined symptoms of i) into two classes including a first class of symptoms representing symptoms most likely experienced by the customer and a second class of symptoms representing symptoms most likely not experienced by the customer,

iii) second data identifying a set of predetermined root causes linked to the set of predetermined symptoms of i),

iv) second interface elements that are configured to allow the user to classify the set of predetermined root causes of iii) into two classes including a first class of root causes representing root causes most likely experienced by the customer and a second class of root causes representing root causes most likely not experienced by the customer, and

v) third data identifying a set of solutions linked to the set of predetermined root causes of iii), wherein the third data identifies a best solution based upon the predetermined root causes of iii) and their associated class designations as dictated by user input with the second interface elements.

36. A knowledge interface according to claim 35, further comprising:

a user input mechanism that is configured to enable the user to specify a natural text description of at least one symptom of the problem or issue experienced by the customer with respect to a particular product or service; and

an interface to an analysis engine that is configured to identify the set of predetermined symptoms, wherein the set of predetermined symptoms are linked by statistical analysis to the natural text description specified by user operation of the user input mechanism.