# US 12,192,410 B1 · System and method for managing routing of customer calls to agents

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- Number: US 12,192,410 B1
- Document ID: US12192410B1
- Status: Granted
- Kind: B1
- Application number: 18/452,991
- Filed: 2023-08-21
- Granted: 2025-01-07
- Earliest claimed: 2017-08-29
- Assignees: Massachusetts Mutual Life Insurance Company
- Applicants: Massachusetts Mutual Life Insurance Company
- Inventors: Sears Merritt
- Web page: https://patentgrep.com/patent/US12192410B1

## CPC

- G06N 5/022: Knowledge engineering; Knowledge acquisition
- G06N 20/20: Ensemble learning
- G06N 5/01: Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
- G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks
- G06N 20/00: Machine learning
- G06Q 10/06311: {Scheduling, planning or task assignment for a person or group}
- G06Q 30/0201: Market modelling; Market analysis; Collecting market data
- G06Q 30/0282: Rating or review of business operators or products
- G06Q 30/0601: Electronic shopping [e-shopping]
- G06Q 40/08: Insurance
- H04M 3/4365: {based on information specified by the calling party, e.g. priority or subject}
- H04M 3/5232: {Call distribution algorithms}
- H04M 3/5233: {Operator skill based call distribution}
- H04M 3/5235: {Dependent on call type or called number [DNIS]}
- H04M 3/42059: {Making use of the calling party identifier}
- H04M 3/42195: {Arrangements for calling back a calling subscriber (when the wanted subscriber ceases to be busy H04M3/48)}
- H04M 3/5183: {Call or contact centers with computer-telephony arrangements}
- H04M 3/5231: {with call back arrangements}
- H04M 2203/556: Statistical analysis and interpretation
- H04M 2203/558: Databases
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- H04M: TELEPHONIC COMMUNICATION (circuits for controlling other apparatus via a telephone cable and not involving telephone switching apparatus G08)

## Abstract

A call management system of a call center retrieves from a customer database enterprise customer data associated with an identified customer in a customer call, which may include customer event data, attributions data, and activity event data. The customer database tracks prospects, leads, new business, and purchasers of an enterprise. The system retrieves customer demographic data associated with the identified customer. A predictive model is selected from a plurality of predictive models based on retrieved enterprise customer data. The selected predictive model, including a logistic regression model, and tree-based model, determines a value prediction signal for the identified customer, then classifies the identified customer into a first value group or a second value group. The system routes a customer call classified in the first value group to a first call queue assignment, and routes a customer call classified in the second value group to a second call queue assignment.

## Claims

### Claim 1

A method for managing customer calls within a call center, comprising:
receiving, by a processor, a customer call at a call center from a customer;
executing, by the processor, a predictive machine learning model configured to output a signal representative of likelihood of purchase of a product by inputting customer data retrieved using an identification of the customer; and
routing, by the processor in accordance with the output signal, the customer call to an agent.

### Claim 2 (depends on 1)

The method of claim 1, wherein the customer data comprises a previously purchased product.

### Claim 3 (depends on 1)

The method of claim 1, further comprising:
transmitting, by the processor, to a device of the agent, information representative of at least one of the customer data or information representative of likelihood of purchase of the product.

### Claim 4 (depends on 1)

The method of claim 1, further comprising:
transmitting, by the processor, to a device of the agent, information representative of customer service interactions with the customer relating to a previously purchased product.

### Claim 5 (depends on 1)

The method of claim 1, wherein the customer data comprises customer demographic data.

### Claim 6 (depends on 1)

The method of claim 1, further comprising:
generating, by the processor, a queue of customer call, wherein each customer call has a position within the queue in accordance with its respective likelihood of purchase of the product.

### Claim 7 (depends on 1)

The method of claim 1, wherein the predictive machine learning model is configured to predict a second signal corresponding to a likelihood of the customer accepting an offer to purchase the product or a second product.

### Claim 8

A system comprising:
a server comprising a processor and a non-transitory computer-readable medium containing instructions that when executed by the processor causes the processor to:
receive a customer call at a call center from a customer;
execute a predictive machine learning model configured to output a signal representative of likelihood of purchase of a product by inputting customer data retrieved using an identification of the customer; and
route, in accordance with the output signal, the customer call to an agent.

### Claim 9 (depends on 8)

The system of claim 8, wherein the customer data comprises a previously purchased product.

### Claim 10 (depends on 8)

The system of claim 8, wherein the instructions are further configured to cause the processor to:
transmit to a device of the agent, information representative of at least one of the customer data or information representative of likelihood of purchase of the product.

### Claim 11 (depends on 8)

The system of claim 8, wherein the instructions are further configured to cause the processor to:
transmit to a device of the agent, information representative of customer service interactions with the customer relating to a previously purchased product.

### Claim 12 (depends on 8)

The system of claim 8, wherein the customer data comprises customer demographic data.

### Claim 13 (depends on 8)

The system of claim 8, wherein the instructions are further configured to cause the processor to:
generate a queue of customer call, wherein each customer call has a position within the queue in accordance with its respective likelihood of purchase of the product.

### Claim 14 (depends on 8)

The system of claim 8, wherein the predictive machine learning model is configured to predict a second signal corresponding to a likelihood of the customer accepting an offer to purchase the product or a second product.

### Claim 15

A system comprising:
a database; and
a computer configured to execute a predictive machine learning model, wherein the computer is communication with the database, the computer further configured to:
receive a customer call at a call center from a customer;
execute the predictive machine learning model configured to output a signal representative of likelihood of purchase of a product by inputting customer data retrieved from the database using an identification of the customer; and
route, in accordance with the output signal, the customer call to an agent.

### Claim 16 (depends on 15)

The system of claim 15, wherein the customer data comprises a previously purchased product.

### Claim 17 (depends on 15)

The system of claim 15, wherein the computer is further configured to:
transmit to a device of the agent, information representative of at least one of the customer data or information representative of likelihood of purchase of the product.

### Claim 18 (depends on 15)

The system of claim 15, wherein the computer is further configured to:
transmit to a device of the agent, information representative of customer service interactions with the customer relating to the previously purchased product.

### Claim 19 (depends on 15)

The system of claim 15, wherein the customer data comprises customer demographic data.

### Claim 20 (depends on 15)

The system of claim 15, wherein the computer is further configured to:
generate a queue of customer call, wherein each customer call has a position within the queue in accordance with its respective likelihood of purchase of the product.