IP Library Granted Patent US 9,807,235
Granted Patent B1
US 9,807,235 · App. 15/625,363 · Granted Oct 31, 2017

Utilizing predictive models to improve predictive dialer pacing capabilities

Inventors: Patrick M. McDaniel (Atlanta, GA); Shang Gao (Atlanta, GA)
Assignee: Noble Systems Corporation
H04M3/5158H04M3/5238
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Quick Facts
Patent No.
US 9,807,235
App. No.
15/625,363
Granted
Oct 31, 2017
Kind
B1
Abstract

Various embodiments of the invention provide methods, systems, and computer-program products for pacing outbound calls placed by a predictive dialer in a contact center. Specifically, an ensemble made up of a global predictive model and a local predictive model is applied to each dialing record found in a plurality of dialing records to provide a probability of an outbound call placed to the dialing record resulting in a live connect. Accordingly, a call pacing hit ratio can then be calculated based on the probability for each of the dialing records and this call pacing hit ratio can be used by a predictive dialer in various embodiments to more accurately pace the placing of outbound calls then by using conventionally derived call pacing hit ratios.

Claims (31)

1. A method for pacing outbound calls placed by a predictive dialer in a contact center, comprising the steps of:

calculating a call pacing hit ratio based on a probability for each dialing record in a plurality of dialing records of an outbound call placed to the dialing record resulting in a live connect, wherein the call pacing hit ratio represents a percentage of outbound calls expected to result in a live connect and the probability for each dialing record is determined by applying an ensemble to the dialing record comprising a global predictive model representing comprehensive dialing trends across at least one of multiple industries, multiple purposes, multiple locations, and multiple predictive dialers and a local predictive model representing a specific dialing history associated with the contact center;

determining a number of outbound calls to place by the predictive dialer based on the call pacing hit ratio and at least one of a number of agents associated with the contact center that are currently available to handle calls and a number of agents associated with the contact center that are expected to become available to handle calls within a time period;

selecting a set of dialing records from the plurality of dialing records by the predictive dialer based on the number of outbound calls to place; and

placing virtually simultaneous outbound calls by the predictive dialer for each of the dialing records found in the set of dialing records.

2. The method of claim 1 , wherein determining the number of outbound calls to place by the predictive dialer is also based on a set target comprising at least one of: maintaining an abandonment rate; maintaining a time limit on how long a party can remain on hold before being connected with an agent; and maintaining a maximum wait time an agent can wait between calls.

3. The method of claim 1 , wherein the ensemble comprising the global predictive model and the local predictive model is generated using one of a technique of bagging, boosting, or stacking.

4. The method of claim 3 , wherein each of the global predictive model and the local predictive model is one of a decision tree, a support vector machine, a Bayesian network, clustering, reinforcement learning, or a neural network.

5. The method of claim 1 , wherein the predictive dialer calculates the call pacing hit ratio by calculating an average for the probabilities across the plurality of dialing records and multiplying the average by a number of dialing records found in the plurality of dialing records.

6. The method of claim 1 , wherein the plurality of dialing records are sorted based on a probability of making a right party contact by placing an outbound call to each of the dialing records found in the plurality of dialing records.

7. A non-transitory, computer-readable storage medium comprising computer-executable instructions for pacing outbound calls placed by a predictive dialer in a contact center that when executed by the predictive dialer are configured to cause the predictive dialer to:

calculate a call pacing hit ratio based on a probability for each dialing record in a plurality of dialing records of an outbound call placed to the dialing record resulting in a live connect, wherein the call pacing hit ratio represents a percentage of outbound calls expected to result in a live connect and the probability for each dialing record is determined by applying an ensemble to the dialing record comprising a global predictive model representing comprehensive dialing trends across at least one of multiple industries, multiple purposes, multiple locations, and multiple predictive dialers and a local predictive model representing a specific dialing history associated with the contact center;

determine a number of outbound calls to place based on the call pacing hit ratio and at least one of a number of agents associated with the contact center that are currently available to handle calls and a number of agents associated with the contact center that are expected to become available to handle calls within a time period;

select a set of dialing records from the plurality of dialing records based on the number of outbound calls to place; and

place virtually simultaneous outbound calls for each of the dialing records found in the set of dialing records.

8. The non-transitory, computer-readable storage medium of claim 7 , wherein the computer-executable instructions cause the predictive dialer to determine the number of outbound calls to place based also on a set target comprising at least one of: maintaining an abandonment rate; maintaining a time limit on how long a party can remain on hold before being connected with an agent; and maintaining a maximum wait time an agent can wait between calls.

9. The non-transitory, computer-readable storage medium of claim 7 , wherein the ensemble comprising the global predictive model and the local predictive model is generated using one of a technique of bagging, boosting, or stacking.

10. The non-transitory, computer-readable storage medium of claim 9 , wherein each of the global predictive model and the local predictive model is one of a decision tree, a support vector machine, a Bayesian network, clustering, reinforcement learning, or a neural network.

11. The non-transitory, computer-readable storage medium of claim 7 , wherein the computer-executable instructions cause the predictive dialer to calculate the call pacing hit ratio by calculating an average for the probabilities across the plurality of dialing records and multiplying the average by a number of dialing records found in the plurality of dialing records.

12. The non-transitory, computer-readable storage medium of claim 7 , wherein the plurality of dialing records are sorted based on a probability of making a right party contact by placing an outbound call to each of the dialing records found in the plurality of dialing records.

13. A system for pacing outbound calls in a contact center, the system comprising:

a predictive dialer configured to:

calculate a call pacing hit ratio based on a probability for each dialing record in a plurality of dialing records of an outbound call placed to the dialing record resulting in a live connect, wherein the call pacing hit ratio represents a percentage of outbound calls expected to result in a live connect and the probability for each dialing record is determined by applying an ensemble to the dialing record comprising a global predictive model representing comprehensive dialing trends across at least one of multiple industries, multiple purposes, multiple locations, and multiple predictive dialers and a local predictive model representing a specific dialing history associated with the contact center;

determine a number of outbound calls to place based on the call pacing hit ratio and at least one of a number of agents associated with the contact center that are currently available to handle calls and a number of agents associated with the contact center that are expected to become available to handle calls within a time period;

select a set of dialing records from the plurality of dialing records based on the number of outbound calls to place; and

place virtually simultaneous outbound calls for each of the dialing records found in the set of dialing records.

14. The system of claim 13 , wherein the predictive dialer is configured to determine the number of outbound calls to place based also on a set target comprising at least one of: maintaining an abandonment rate; maintaining a time limit on how long a party can remain on hold before being connected with an agent; and maintaining a maximum wait time an agent can wait between calls.

15. The system of claim 13 , wherein the ensemble comprising the global predictive model and the local predictive model is generated using one of a technique of bagging, boosting, or stacking.

16. The system of claim 15 , wherein each of the global predictive model and the local predictive model is one of a decision tree, a support vector machine, a Bayesian network, clustering, reinforcement learning, or a neural network.

17. The system of claim 13 , wherein the predictive dialer is configured to calculate the call pacing hit ratio by calculating an average for the probabilities across the plurality of dialing records and multiplying the average by a number of dialing records found in the plurality of dialing records.

18. The system of claim 13 , wherein the plurality of dialing records are sorted based on a probability of making a right party contact by placing an outbound call to each of the dialing records found in the plurality of dialing records.

Assignments (13)
RELEASE OF SECURITY INTEREST Recorded Oct 27, 2025
From: JEFFERIES FINANCE LLC, AS COLLATERAL AGENT
To: ALVARIA CAYMAN (WEM); ALVARIA CAYMAN (CXIP)
Reel/Frame 073360/0209 →
ASSIGNMENT Recorded Oct 27, 2025
From: ALVARIA CAYMAN (WEM); ALVARIA CAYMAN (CXIP); NOBLE SYSTEMS, LLC
To: ALVARIA, INC.
Reel/Frame 073360/0481 →
SECURITY INTEREST Recorded Oct 27, 2025
From: ALVARIA, INC.
To: JEFFERIES FINANCE LLC, AS COLLATERAL AGENT
Reel/Frame 073360/0564 →
RELEASE OF SECURITY INTEREST Recorded Mar 20, 2024
From: JEFFRIES FINANCE LLC
To: ALVARIA, INC.; NOBLE SYSTEMS, LLC
Reel/Frame 066850/0384 →
RELEASE OF SECURITY INTEREST Recorded Mar 20, 2024
From: JEFFRIES FINANCE LLC
To: ALVARIA, INC.; NOBLE SYSTEMS, LLC
Reel/Frame 066850/0428 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 20, 2024
From: NOBLE SYSTEMS, LLC
To: ALVARIA CAYMAN (CX)
Reel/Frame 066850/0556 →
PATENT SECURITY AGREEMENT Recorded Mar 20, 2024
From: ALVARIA CAYMAN (WEM); ALVARIA CAYMAN (CXIP)
To: JEFFERIES FINANCE LLC
Reel/Frame 066850/0334 →
CERTIFICATE OF CONVERSION Recorded Mar 12, 2024
From: NOBLE SYSTEMS CORPORATION, A GEORGIA CORPORATION
To: NOBLE SYSTEMS, LLC, A DELAWARE LIMITED LIABILITY COMPANY
Reel/Frame 066794/0435 →
RELEASE OF SECURITY INTEREST Recorded May 10, 2021
From: WELLS FARGO CAPITAL FINANCE, LLC
To: NOBLE SYSTEMS CORPORATION
Reel/Frame 056193/0363 →
SECOND LIEN PATENT SECURITY AGREEMENT Recorded May 6, 2021
From: NOBLE SYSTEMS CORPORATION; ASPECT SOFTWARE, INC.
To: JEFFERIES FINANCE LLC
Reel/Frame 057674/0664 →
FIRST LIEN PATENT SECURITY AGREEMENT Recorded May 6, 2021
From: NOBLE SYSTEMS CORPORATION; ASPECT SOFTWARE, INC.
To: JEFFERIES FINANCE LLC
Reel/Frame 057261/0093 →
SECURITY INTEREST Recorded Apr 23, 2020
From: NOBLE SYSTEMS CORPORATION
To: WELLS FARGO CAPITAL FINANCE, LLC
Reel/Frame 052495/0287 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 16, 2017
From: MCDANIEL, PATRICK M; GAO, SHANG
To: NOBLE SYSTEMS CORPORATION
Reel/Frame 042734/0760 →
Continuity (1)
Continuation 15270425 · Sep 20, 2016