IP Library Granted Patent US 10,582,054
Granted Patent B2
US 10,582,054 · App. 15/611,753 · Granted Mar 3, 2020

Dynamic recommendation of routing rules for contact center use

Inventor: Vyacheslav Zhakov (Burlingame, CA)
H04M3/5175G06Q30/016G06Q30/02H04M3/5183H04M2203/402
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Quick Facts
Patent No.
US 10,582,054
App. No.
15/611,753
Granted
Mar 3, 2020
Kind
B2
Abstract

A machine learning system and method for contact center use. Activities associated with a plurality of contact centers are monitored and a knowledge base is updated based on the monitored activities. An outcome for a particular contact center may be predicted based on monitored interactions for the particular contact center, and based on information in the knowledge base. An output is then generated based on the predicted outcome.

Claims (34)

1. A method for recommending routing strategies to contact centers, the method comprising:

identifying, by a processor, one or more customer satisfaction predictors;

monitoring, by the processor, activities associated with a plurality of contact centers, and identifying outcomes of the activities;

updating, by the processor, a machine learning model stored in a knowledge base based on the monitored activities, the identified outcomes of the activities, and the identified customer satisfaction predictors;

assessing, by the processor, a particular outcome produced in response to invoking a current routing strategy for processing a particular interaction for a particular contact center;

in response to the assessing, automatically selecting a candidate routing strategy from the knowledge base based on the updated machine learning mode;

testing the selected candidate routing strategy with the particular interaction;

in response to the testing, recommending the candidate routing strategy for the contact center, wherein the recommended candidate routing strategy includes computer instructions for controlling routing of a future interaction to a resource of the particular contact center; and

establishing, by an edge device, a communication session between the resource and a particular end user device based on execution of the computer instructions.

2. The method of claim 1 , wherein the monitored activities are customer interactions handled by the plurality of contact centers.

3. The method of claim 1 , wherein the monitored activities include an amount of time a call is put on hold prior to being routed to an agent.

4. The method of claim 1 , wherein the monitored activities include a number of transfers made during a call.

5. The method of claim 1 , wherein the particular outcome is feedback from a customer associated with the particular interaction indicative of lack of satisfaction by a customer associated with the particular interaction.

6. The method of claim 1 , wherein the particular outcome is abandonment of the call.

7. The method of claim 1 , wherein the updating includes adjusting parameters to the machine learning model based on the monitored activities.

8. The method of claim 1 further comprising:

deploying the recommended routing strategy in response to a user command.

9. The method of claim 1 further comprising:

automatically deploying the recommended routing strategy.

10. A machine learning system for contact center use, the machine learning system comprising:

one or more processors; and

one or more memory devices coupled to the one or more processors and having program instructions stored therein, the one or more processors being configured to execute the program instructions, the program instructions comprising:

identifying one or more customer satisfaction predictors;

monitoring activities associated with a plurality of contact centers, and identifying outcomes of the activities;

updating a machine learning model stored in a knowledge base based on the monitored activities, the identified outcomes of the activities, and the identified customer satisfaction predictors;

assessing a particular outcome produced in response to invoking a current routing strategy for processing a particular interaction for a particular contact center;

in response to the assessing, automatically selecting a candidate routing strategy from the knowledge base based on the updated machine learning mode;

testing the selected candidate routing strategy with the particular interaction; and

in response to the testing, recommending the candidate routing strategy for the contact center, wherein the recommended candidate routing strategy includes computer instructions for controlling routing of a future interaction to a resource of the particular contact center; and

an edge device coupled to the one or more processors configured to establish a communication session between the resource and a particular end user device based on execution of the routing instructions.

11. The system of claim 10 , wherein the monitored activities are customer interactions handled by the plurality of contact centers.

12. The system of claim 10 , wherein the monitored activities include an amount of time a call is put on hold prior to being routed to an agent.

13. The system of claim 10 , wherein the monitored activities include a number of transfers made during a call.

14. The system of claim 10 , wherein the particular outcome is feedback from a customer associated with the particular interaction indicative of lack of satisfaction by a customer associated with the particular interaction.

Assignments (4)
NOTICE OF SUCCESSION OF SECURITY INTERESTS AT REEL/FRAME 04814/0387 Recorded Feb 5, 2025
From: BANK OF AMERICA, N.A., AS RESIGNING AGENT
To: GOLDMAN SACHS BANK USA, AS SUCCESSOR AGENT
Reel/Frame 070115/0445 →
CHANGE OF NAME Recorded May 13, 2024
From: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.
To: GENESYS CLOUD SERVICES, INC.
Reel/Frame 067391/0089 →
SECURITY AGREEMENT Recorded Feb 22, 2019
From: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.; ECHOPASS CORPORATION; GREENEDEN U.S. HOLDINGS II, LLC
To: BANK OF AMERICA, N.A., AS COLLATERAL AGENT
Reel/Frame 048414/0387 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 19, 2017
From: ZHAKOV, VYACHESLAV
To: GENESYS TELECOMMUNICATIONS LABORATORIES, INC.
Reel/Frame 043042/0014 →
Continuity (2)
Continuation 13684053 · Nov 21, 2012
Related Publication 20170272574A1 · Sep 21, 2017
Cited By (1)
US 12,219,095