IP Library Granted Patent US 12,278,930
Granted Patent B2
US 12,278,930 · App. 17/665,978 · Granted Apr 15, 2025

System and method of real-time wiki knowledge resources

Inventors: Tomas Gorny (Scottsdale, AZ); Dallas Barabasz-Lynn (Gilbert, AZ)
Assignee: Nextiva, Inc.
H04M3/5233G06Q30/016G06Q30/02H04M3/5166H04M3/5175H04M3/5191H04M3/5237
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,278,930
App. No.
17/665,978
Granted
Apr 15, 2025
Kind
B2
Abstract

A system and method are disclosed for recommending a resource to a customer service representative that includes one or more databases that store data describing electronic communication between one or more customer system communication devices and one or more service center communication devices. Embodiments further include a computer coupled with one or more databases and configured to monitor communication activity to determine whether a customer service ticket has been opened between one or more customer system communication devices and one or more service center communication devices and determine a customer service representative score based on one or more customer service representative ranking factors.

Claims (62)

1. A system for managing service centers comprising a server communicatively coupled to a customer system and a service center over a network, the server further comprising:

a computer coupled with a database and comprising a processor and memory, the computer configured to:

monitor one or more channels of communication between one or more customers and a service center for one or more communications between at least one customer of the one or more customers and the service center, wherein the one or more communications each correspond with a customer service ticket;

track factors detailing a resolution of each customer service ticket, wherein the factors are associated with a particular customer service representative (CSR) out of a plurality of customer service representatives (CSRs);

detect, in response to the monitoring the one or more communication channels, a communication between a customer and the service center;

retrieve, in response to the detecting, a plurality of customer factors characterizing the customer;

score each customer service representative (CSR) based on a corresponding weight applied to each of the tracked factors and each of a plurality of other factors associated with each customer service representative (CSR) to generate a single customer service representative (CSR) score;

receive a manual adjustment of the single customer service representative (CSR) score;

identify a customer service representative (CSR) out of the plurality of customer service representatives (CSRs) whose score indicates a best match with the customer;

assign the customer to the customer service representative (CSR) based on the identifying;

route the communication from the customer to a communication device associated with the assigned customer service representative (CSR) at the service center;

monitor an accuracy of the matching between the customer service representative (CSR) and the customer; and

in response to the monitored accuracy not improving over time, adjust one or more of the corresponding weights applied to each of the tracked factors to improve the matching between the customer service representative (CSR) and the customer.

2. The system of claim 1 , wherein the computer is further configured to:

score the plurality of customer service representatives (CSRs) based on the plurality of other factors having a match with corresponding customer factors.

3. The system of claim 1 , wherein one or more tracked performance metrics further comprise: a customer ticket completion speed and a proportion of reopened customer tickets.

4. The system of claim 2 , wherein the plurality of other factors further comprise at least one category selected from the group consisting of:

an age group, a gender and an educational level.

5. The system of claim 1 , wherein the scoring each customer service representative (CSR) further comprises:

generate a composite score based on summing the weighted tracked factors and the weighted other factors.

6. The system of claim 1 , wherein the computer is further configured to:

update the tracked factors based on results of a survey received from the customer.

7. A computer-implemented method for managing service centers comprising:

monitoring one or more channels of communication between one or more customers and a service center for one or more communications between at least one customer of the one or more customers and the service center, wherein the one or more communications each correspond with a customer service ticket;

tracking factors detailing a resolution of each customer service ticket, wherein the factors are associated with a particular customer service representative (CSR) out of a plurality of customer service representatives (CSRs);

detecting, in response to the monitoring the one or more communication channels, a communication between a customer and the service center;

retrieving, in response to the detecting, a plurality of customer factors characterizing the customer;

scoring each customer service representative (CSR) based on a corresponding weight applied to each of the tracked factors and each of a plurality of other factors associated with each customer service representative (CSR) to generate a single customer service representative (CSR) score;

receiving a manual adjustment of the single customer service representative (CSR) score;

identifying a customer service representative (CSR) out of the plurality of customer service representatives (CSRs) whose score indicates a best match with the customer;

assigning the customer to the customer service representative (CSR) based on the identifying;

routing the communication from the customer to a communication device associated with the assigned customer service representative (CSR) at the service center;

monitoring an accuracy of the matching between the customer service representative (CSR) and the customer; and

in response to the monitored accuracy not improving over time, adjusting one or more of the corresponding weights applied to each of the tracked factors to improve the matching between the customer service representative (CSR) and the customer.

8. The method of claim 7 , wherein the method further comprises:

scoring the plurality of customer service representatives (CSRs) based on the plurality of other factors having a match with corresponding customer factors.

9. The method of claim 7 , wherein one or more tracked performance metrics further comprise: a customer ticket completion speed and a proportion of reopened customer tickets.

10. The method of claim 8 , wherein the plurality of other factors further comprise at least one category selected from the group consisting of:

an age group, a gender and an educational level.

11. The method of claim 7 , wherein the scoring each customer service representative (CSR) further comprises:

generating a composite score based on summing the weighted tracked factors and the weighted other factors.

12. The method of claim 7 , wherein the method further comprises:

update the tracked factors based on results of a survey received from the customer.

13. A non-transitory computer-readable medium embodied with software for managing service centers, the software when executed using one or more computer systems is programmed to:

monitor one or more channels of communication between one or more customers and a service center for one or more communications between at least one customer of the one or more customers and the service center, wherein the one or more communications each correspond with a customer service ticket;

track factors detailing a resolution of each customer service ticket, wherein the factors are associated with a particular customer service representative (CSR) out of a plurality of customer service representatives (CSRs);

detect, in response to the monitoring the one or more communication channels, a communication between a customer and the service center;

retrieve, in response to the detecting, a plurality of customer factors characterizing the customer;

score each customer service representative (CSR) based on a corresponding weight applied to each of the tracked factors and each of a plurality of other factors associated with each customer service representative (CSR) to generate a single customer service representative (CSR) score;

receive a manual adjustment of the single customer service representative (CSR) score;

identify a customer service representative (CSR) out of the plurality of customer service representatives (CSRs) whose score indicates a best match with the customer;

assign the customer to the customer service representative (CSR) based on the identifying;

route the communication from the customer to a communication device associated with the assigned customer service representative (CSR) at the service center;

monitor an accuracy of the matching between the customer service representative (CSR) and the customer; and

in response to the monitored accuracy not improving over time, adjust one or more of the corresponding weights applied to each of the tracked factors to improve the matching between the customer service representative (CSR) and the customer.

14. The non-transitory computer-readable medium of claim 13 , wherein the software is further programmed to:

score the plurality of customer service representatives (CSRs) based on the plurality of other factors having a match with corresponding customer factors.

15. The non-transitory computer-readable medium of claim 13 , wherein one or more tracked performance metrics further comprise: a customer ticket completion speed and a proportion of reopened customer tickets.

16. The non-transitory computer-readable medium of claim 14 , wherein the plurality of other factors further comprise at least one category selected from the group consisting of:

an age group, a gender and an educational level.

17. The non-transitory computer-readable medium of claim 14 , wherein the software is further programmed to:

update the tracked factors based on results of a survey received from the customer.

Assignments (3)
CORRECTIVE ASSIGNMENT TO CORRECT THE CORRECT THE PROPERTY NUMBERS PREVIOUSLY RECORDED AT REEL: 67172 FRAME: 404. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Apr 23, 2024
From: NEXTIVA, INC.; THRIO, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS ADMINISTRATIVE AGENT
Reel/Frame 067308/0183 →
SECURITY INTEREST Recorded Apr 19, 2024
From: NEXTIVA, INC.; THRIO, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS ADMINISTRATIVE AGENT
Reel/Frame 067172/0404 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 9, 2022
From: GORNY, TOMAS; BARABASZ-LYNN, DALLAS
To: NEXTIVA, INC.
Reel/Frame 058941/0951 →
Continuity (4)
Continuation 16940097 · Jul 27, 2020
Continuation 16591326 · Oct 2, 2019
Provisional Application 62783353 · Dec 21, 2018
Related Publication 20220159124A1 · May 19, 2022
References Cited (48)
US 5825869A · Brooks · 1998 [cited by examiner]
US 6430558B1 · Delano · 2002 [cited by applicant]
US 6459788B1 · Khuc et al. · 2002 [cited by applicant]
US 6859783B2 · Cogger et al. · 2005 [cited by applicant]
US 7885913B2 · Weber et al. · 2011 [cited by applicant]
US 8027458B1 · Pollock · 2011 [cited by applicant]
US 8065173B2 · Abu-Hakima et al. · 2011 [cited by applicant]
US 8184797B1 · Rosen · 2012 [cited by applicant]
US 8300797B1 · Benesh et al. · 2012 [cited by applicant]
US 8311863B1 · Kemp · 2012 [cited by applicant]
US 8341081B1 · Wang et al. · 2012 [cited by applicant]
US 8724797B2 · Chishti et al. · 2014 [cited by applicant]
US 8781882B1 · Arboletti et al. · 2014 [cited by applicant]
US 8789053B2 · Howard · 2014 [cited by applicant]
US 8880430B1 · Wang et al. · 2014 [cited by applicant]
US 9075802B2 · Davis et al. · 2015 [cited by applicant]
US 9215323B2 · Chishti · 2015 [cited by applicant]
US 9253320B2 · Fan et al. · 2016 [cited by applicant]
US 10084919B2 · Dervan et al. · 2018 [cited by applicant]
US 10223646B1 · Vontobel et al. · 2019 [cited by applicant]
US 10614468B2 · Vedula · 2020 [cited by applicant]
US 10764440B2 · Gomy et al. · 2020 [cited by applicant]
US 10805465B1 · Krebs · 2020 [cited by examiner]
US 10810600B2 · Adrian et al. · 2020 [cited by applicant]
US 10861110B2 · Chen et al. · 2020 [cited by applicant]
US 10970291B2 · McNeela et al. · 2021 [cited by applicant]
US 11023774B2 · Nefedov · 2021 [cited by applicant]
US 20020123983A1 · Riley · 2002 [cited by examiner]
US 20020188527A1 · Dillard et al. · 2002 [cited by applicant]
US 20030220860A1 · Heytens et al. · 2003 [cited by applicant]
US 20040042611A1 · Power et al. · 2004 [cited by applicant]
US 20090043669A1 · Hibbets et al. · 2009 [cited by applicant]
US 20100020961A1 · Spottiswoode · 2010 [cited by applicant]
US 20120051536A1 · Chishti · 2012 [cited by examiner]
US 20120224680A1 · Spottiswoode · 2012 [cited by examiner]
US 20130039483A1 · Wolfeld · 2013 [cited by examiner]
US 20130173521A1 · Pirlet et al. · 2013 [cited by applicant]
US 20140278646A1 · Adrian · 2014 [cited by examiner]
US 20150269586A1 · Garia et al. · 2015 [cited by applicant]
US 20160269554A1 · Cecchi · 2016 [cited by examiner]
US 20160292802A1 · Tada et al. · 2016 [cited by applicant]
US 20200034689A1 · Andrassy et al. · 2020 [cited by applicant]
US 20200097608A1 · Xiu et al. · 2020 [cited by applicant]
US 20200358902A1 · Gomy et al. · 2020 [cited by applicant]
WO 2012142341 · 2012 [cited by applicant]
EP Examination Report; EP Application No. 19900260; Jan. 30, 2023; 14 pages. [cited by applicant]
Anonymous: “Manual:Creating a bot—MediaWiki”, Jul. 28, 2018 (Jul. 28, 2018), XP093017147, Retrieved from the Internet: URL: https://mediawiki.org/w/index.php?title=Manual:Creating_a_bot&oldid=2839131 [retrieved on Jan. … [cited by applicant]
International Search Report for Application No. PCT/US19/62667 dated Feb. 7, 2020. 3 Page. [cited by applicant]