Systems and methods for navigating vehicle inventory

Patent metadata

Field	Value
Publication number	US-2024314384-A1
Application number	US-202418650372-A
Country	US
Kind code	A1
Filing date	Apr 30, 2024
Priority date	Oct 18, 2019
Publication date	Sep 19, 2024
Grant date	—

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.

First claim

What is claimed is:

1 . A system comprising:
a user device displaying a user interface, wherein the user interface receives vehicle selection terms via an input device operably connected to the user device; a data storage server containing vehicle inventory data; and an application communicatively connected to the user interface and the data storage server, wherein the application:
receives vehicle selection terms from the user interface;
receives vehicle inventory data from the data storage server; and
transmits an alert to the user interface upon detecting a change to the vehicle inventory data which is associated with the vehicle selection terms.

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

3 . The system of claim 1 , wherein the application is configured to automatically execute an application update without input from a user.

4 . The system of claim 1 , wherein the user interface receives payment criteria from a user.

5 . The system of claim 4 , wherein the application transmits an alert to the user interface upon identifying a vehicle from the vehicle inventory data that satisfies the vehicle selection terms and payment criteria.

6 . The system of claim 1 , wherein the application records user interface activity and applies a predictive model to the user interface activity to determine a subsequent action.

7 . The system of claim 6 , wherein the predictive model is built by machine learning using at least one algorithm selected from the group of gradient boosting machine, logistic regression, and neural networks.

8 . The system of claim 7 wherein the subsequent action comprises at least one selected from the group of updating the vehicle selection terms, sending a notice to a third party, sending a request to a third party, sending an alert to the user; or sending an incentive offer to the user.

9 . The system of claim 1 , wherein the user interface receives credit information from the user.

10 . The system of claim 9 , wherein, upon receipt of a pre-approval request, the application applies a predictive model to the received credit information and vehicle selection terms to determine whether to present a pre-approved offer of credit to the user.

11 . The system of claim 10 , wherein upon determining to present a pre-approved offer of credit to the user, the user interface displays price and financing information associated with a vehicle to the user.

12 . The system of claim 11 , wherein, upon displaying price and financing information to a user, the application prompts the user to select a preferred vehicle.

13 . The system of claim 11 , wherein, prior to displaying price information, the application sends a price adjustment request to a vehicle dealer.

14 . The system of claim 10 , wherein upon determining to present a pre-approved offer of credit to the user, the application transmits the vehicle selection terms to a vehicle dealer.

15 . A method comprising:
receiving vehicle selection criteria via a user interface, wherein the user interface is displayed on a user device; receiving vehicle inventory data from a database, wherein the vehicle inventory data comprises information associated with a vehicle; selecting at least one vehicle from the vehicle inventory data based on the vehicle selection criteria; displaying information associated with a selected vehicle on the user device; and alerting a user to changes in the vehicle inventory data associated with the vehicle selection criteria.

16 . The method of claim 15 , further comprising:
receiving credit information from via the user interface; applying a predictive model to the received credit information and vehicle selection criteria to determine whether to present a pre-approved offer of credit; and displaying pricing information associated with a selected vehicle upon determining to present a pre-approved offer of credit to the user.

17 . The method of claim 15 , further comprising: after displaying information associated with a selected vehicle, receiving a preferred vehicle selection.

18 . The method of claim 17 , further comprising: applying a predictive model to the received vehicle selection criteria, preferred vehicle selection, and vehicle inventory data to develop suggested vehicle criteria and displaying information associated with at least one vehicle based on the suggested vehicle criteria.

19 . The method of claim 15 , further comprising:
recording user activity and taking subsequent action based on the user activity, wherein the subsequent action comprises one of updating the vehicle selection criteria, sending an alert to a third party, sending a request to a third party, sending an alert to the user; or sending an incentive offer to the user.

20 . A user retention system comprising:
a user device comprising at least one input device; a user interface, wherein the user interface receives vehicle selection criteria and financing information from a user; a vehicle inventory database communicatively connected to the user interface wherein the vehicle inventory database contains vehicle information; and an application communicatively connected to the user interface, wherein the application:
receives vehicle selection criteria and financing information from the user interface;
receives vehicle information from the vehicle inventory database;
applies a predictive model to the received vehicle selection criteria, financing information, and vehicle information to determine whether to present a pre-approved offer of credit to the user;
upon determining to present a pre-approved offer of credit to the user, displays vehicle information to the user; and
sends an alert to the user interface upon detecting a change to the vehicle information associated with the vehicle selection criteria.

Assignees

• Capital One Services Llc

Inventors

• Deshpande Amit
• Mathews Liju
• Chikkaveerappa Satish
• Venuraju Mithra

Classifications

• G06Q30/06

  Buying, selling or leasing transactions · CPC title

• G06Q10/08 Primary

  Logistics, e.g. warehousing, loading or distribution; Inventory or stock management · CPC title

• H04N21/251

  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) · CPC title

• G07C5/008

  communicating information to a remotely located station (transmission systems for measured values G08C) · CPC title

• G06F16/9535

  Search customisation based on user profiles and personalisation · CPC title