# US 12,003,802 B2 · System, method, and computer-readable medium for navigating vehicle inventory

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- Number: US 12,003,802 B2
- Document ID: US12003802B2
- Status: Granted
- Kind: B2
- Application number: 17/509,515
- Filed: 2021-10-25
- Published: 2022-02-10
- Granted: 2024-06-04
- Earliest claimed: 2019-10-18
- Assignees: Capital One Services, LLC
- Applicants: Capital One Services, LLC
- Inventors: Amit Deshpande; Liju Mathews; Satish Chikkaveerappa; Mithra Kosur Venuraju
- Web page: https://patentgrep.com/patent/US12003802B2

## CPC

- H04N 21/41422: {located in transportation means, e.g. personal vehicle (arrangements specially adapted for transportation systems in broadcast systems H04H20/62)}
- G06F 16/9535: Search customisation based on user profiles and personalisation
- G06Q 10/08: Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q 30/06: Buying, selling or leasing transactions
- G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)}
- H04N 21/251: {Learning process for intelligent management, e.g. learning user preferences for recommending movies (details of learning user preferences for the retrieval of video data in a video database G06F16/739; computer systems using learning methods G06N3/08)}
- H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- 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
- G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE

## Abstract

Embodiments of the present disclosure provide systems, methods, and devices for utilizing an application to alert a user to detected changes to inventory data. Example embodiments relate to a predictive model and development of a predictive model using machine learning techniques. Example embodiments of systems and methods may utilize web-based applications and plug-ins, extensions, or add-ons thereof for facilitating communication and presenting dynamic information to a user.

## Claims

### Claim 1

A method performed by an application, the method comprising:
recording, using an activity plugin, user interface activity on a user interface displayed on a user device;
determining suggested vehicle selection terms based on the user interface activity;
receiving vehicle inventory data from a data storage server;
modifying vehicle selection criteria based on the suggested vehicle selection terms and the vehicle inventory data;
monitoring, using an inventory plugin, the vehicle inventory data stored by the data storage server for changes associated with the modified vehicle selection criteria;
determining, using the inventory plugin, a change to the vehicle inventory data which is associated with the modified vehicle selection criteria;
transmitting an alert to the user device via the user interface;
generating an icon indicating push notifications, a drop-down menu, or a pop-up display overlaying the user interface displayed on the user device in response to the alert; and
monitoring, using the inventory plugin, the vehicle inventory data for one or more updated changes associated with the modified vehicle selection criteria,
wherein the application is configured to operate in the background until the determination of the change to the vehicle inventory data by the inventory plugin.

### Claim 2 (depends on 1)

The method of claim 1, wherein the application is configured to store the user interface activity using the activity plugin.

### Claim 3 (depends on 1)

The method of claim 1, wherein:
determining suggested vehicle terms based on the user interface activity comprises applying a predictive model to the user interface activity, and
the predictive model is developed by machine learning using at least one algorithm selected from the group of gradient boosting machine, logistic regression, and neural networks.

### Claim 4 (depends on 3)

The method of claim 3, wherein the predictive model is developed using historical data associated with at least one selected from the group of a vehicle, vehicle inventory data, user information, user activity, user credit information, vehicle selection terms, and vehicle sales information.

### Claim 5 (depends on 3)

The method of claim 3, further comprising:
receiving credit information via the user interface;
applying the predictive model to the received credit information and the modified vehicle selection criteria to determine whether to present a pre-approved offer of credit; and
displaying pricing information associated with the selected vehicle upon determining to present the pre-approved offer of credit.

### Claim 6 (depends on 3)

The method of claim 3, further comprising using the predictive model to determine an event for the inventory plugin to determine the alert.

### Claim 7 (depends on 3)

The method of claim 3, further comprising determining payment criteria based on the user interface activity by applying the predictive model to the user interface activity.

### Claim 8 (depends on 3)

The method of claim 3, further comprising:
storing user interface activity using the activity plugin,
wherein the user interface activity includes activity performed on a website.

### Claim 9 (depends on 1)

The method of claim 1, wherein:
the vehicle inventory data comprises information associated with a vehicle, and
the inventory plugin is configured to determine the change to the vehicle inventory data by accessing an application programming interface.

### Claim 10 (depends on 1)

The method of claim 1, wherein the suggested vehicle selection terms comprise at least one selected from the group of vehicle make, vehicle model, vehicle year, vehicle features, price, and location.

### Claim 11

A system, comprising:
a user interface displayed on a user device; and
an application communicatively connected to the user interface and a data storage server, wherein the application is configured to:
record, using an activity plugin, user interface activity on the user interface displayed on the user device;
determine suggested vehicle selection terms based on the user interface activity;
receive vehicle inventory data from a data storage server;
modify vehicle selection criteria based on the suggested vehicle selection terms and the vehicle inventory data;
monitor, using an inventory plugin, the vehicle inventory data stored by the data storage server for changes associated with the modified vehicle selection criteria;
determine, using the inventory plugin, a change to the vehicle inventory data which is associated with the modified vehicle selection criteria;
transmit an alert to the user device via the user interface;
generate an icon indicating push notifications, a drop-down menu, or a pop-up display overlaying the user interface displayed on the user device in response to the alert; and
monitor, using the inventory plugin, the vehicle inventory data for one or more updated changes associated with the modified vehicle selection criteria,
wherein the application is configured to operate in the background until the determination of the change to the vehicle inventory data by the inventory plugin.

### Claim 12 (depends on 11)

The system of claim 11, wherein the application is further configured to store the user interface activity using the activity plugin.

### Claim 13 (depends on 11)

The system of claim 11, wherein:
the user interface is configured to receive vehicle selection terms via an input device operably connected to the user device, and
the vehicle selection terms comprise at least one selected from the group of vehicle make, vehicle model, vehicle year, vehicle features, price, and location.

### Claim 14 (depends on 11)

The system of claim 11, wherein:
the application is further configured to determine vehicle selection terms based on the user interface activity by applying a predictive model to the user interface activity, and
the predictive model is developed by machine learning using at least one algorithm selected from the group of gradient boosting machine, logistic regression, and neural networks.

### Claim 15 (depends on 14)

The system of claim 14, wherein the predictive model is developed using historical data associated with at least one selected from the group of a vehicle, vehicle inventory data, user information, user activity, user credit information, vehicle selection terms, and vehicle sales information.

### Claim 16 (depends on 14)

The system of claim 14, wherein the application uses the predictive model to determine an event for the inventory plugin to determine the alert.

### Claim 17 (depends on 16)

The system of claim 16, wherein the event comprises at least one selected from the group of the announcement of a price for a new vehicle, a change in price of a vehicle, a change in availability of a vehicle, a change in expected availability of a vehicle, a change in financing options of a vehicle, a change in location of a vehicle, and a change in trade-in status of a vehicle.

### Claim 18 (depends on 14)

The system of claim 14, wherein:
the user interface is configured to receive payment criteria, and
the application is further configured to:
determine suggested payment criteria based on the user interface activity by applying the predictive model to the user interface activity, and
modify the payment criteria based on the suggested payment criteria.

### Claim 19 (depends on 11)

The system of claim 11, wherein the application is configured to automatically execute an application update without input from a user.

### Claim 20

A non-transitory computer-readable medium containing instructions that, when executed by a processor, configure the processor to perform procedures comprising:
recording, using an activity plugin, user interface activity on a user interface displayed on a user device;
determining suggested vehicle selection terms based on the user interface activity;
receiving vehicle inventory data from a data storage server;
modifying vehicle selection criteria based on the suggested vehicle selection terms and the vehicle inventory data;
monitoring, using an inventory plugin, the vehicle inventory data stored by the data storage server for changes associated with the modified vehicle selection criteria;
determining, using the inventory plugin, a change to the vehicle inventory data which is associated with the modified vehicle selection criteria;
transmitting an alert to the user device via the user interface;
generating an icon indicating push notifications, a drop-down menu, or a pop-up display overlaying the user interface displayed on the user device in response to the alert; and
monitor, using the inventory plugin, the vehicle inventory data for one or more updated changes associated with the modified vehicle selection criteria,
wherein the procedures are configured to operate in the background until the determination of the change to the vehicle inventory data by the inventory plugin.