Systems and methods for determining and leveraging geography-dependent relative desirability of products

Patent metadata

Field	Value
Publication number	US-2024273596-A1
Application number	US-202418581889-A
Country	US
Kind code	A1
Filing date	Feb 20, 2024
Priority date	Apr 20, 2020
Publication date	Aug 15, 2024
Grant date	—

Abstract

According to certain aspects of the disclosure, a computer-implemented method may be used for regulating vehicle stock. The method may include receiving one or more queries indicative of one or more characteristics of a vehicle for purchase by a user and determining based on the one or more queries indicative of the one or more characteristics of the vehicle, at least one vehicle available for purchase at a location of a merchant. The method may also include determining a quantity of the at least one vehicle purchased and assigning a value to the at least one vehicle based on the quantity of the at least one vehicle purchased and a quantity of received queries about the vehicle. The method may also include transmitting the value to the user, with a recommendation regarding the at least one vehicle available for purchase based on the value.

First claim

1 - 20 . (canceled)

21 . A computer-implemented method for regulating vehicle stock, the method comprising:
receiving, by one or more processors, query data including one or more queries indicative of one or more characteristics of one or more vehicles; receiving, by the one or more processors, from a database, transaction data including a quantity of the one or more vehicles that were purchased or attempted to be purchased; monitoring, by the one or more processors, vehicle inventory of a merchant; determining, by the one or more processors, using at least one trained machine learning model, a desirability value and a recommendation for each vehicle of the vehicle inventory of the merchant based on the query data and the transaction data; and transmitting, by the one or more processors, the recommendation to a graphical user interface of the merchant.

22 . The computer-implemented method of claim 21 , wherein the query data includes data indicating vehicle preferences, including at least one of a vehicle year, a vehicle make, a vehicle model, a vehicle color, a vehicle type, a vehicle transmission, a vehicle door count, or a vehicle condition.

23 . The computer-implemented method of claim 21 , wherein the recommendation is based on at least one of a purchasers financial status including a credit profile and at least one of a credit score, a debt amount, a credit segmentation, or a pre-approved loan amount.

24 . The computer-implemented method of claim 21 , wherein the transaction data including the quantity of the one or more vehicles that were purchased or attempted to be purchased comprises vehicles within a predetermined distance of a location of the merchant or within a predetermined time period.

25 . The computer-implemented method of claim 21 , wherein the transaction data includes data indicating one or more loan instruments associated with the quantity of the one or more vehicles that were purchased or attempted to be purchased.

26 . The computer-implemented method of claim 21 , wherein the transaction data includes data indicating an available inventory of merchants in a predetermined area associated with the quantity of the one or more vehicles that were purchased or attempted to be purchased.

27 . The computer-implemented method of claim 21 , wherein determining the desirability value for each vehicle of the vehicle inventory of the merchant is based on a number of vehicles purchased in a predetermined historical period.

28 . The computer-implemented method of claim 21 , wherein determining the desirability value for each vehicle of the vehicle inventory of the merchant further includes learning relationships between demographics of purchasers by the at least one trained machine learning model learning.

29 . The computer-implemented method of claim 21 , wherein the query data includes at least one of a mileage, a total price, a monthly payment, a vehicle category, a body style, a condition, a feature, a fuel economy, a drive type, a specification, a zip code, or a selected one or more merchants of a plurality of merchants.

30 . The computer-implemented method of claim 21 , wherein the recommendation includes adjusting the vehicle inventory of the merchant based on the desirability value for each vehicle of the vehicle inventory of the merchant.

31 . A computer-implemented method for regulating vehicle stock, the method comprising:
receiving, by one or more processors, query data including one or more queries indicative of one or more characteristics of one or more vehicles; receiving, by the one or more processors, from a database, transaction data including a quantity of the one or more vehicles that were purchased or attempted to be purchased; monitoring, by the one or more processors, vehicle inventory of a merchant; determining, by the one or more processors, using at least one trained machine learning model, a desirability value and a recommendation for each vehicle of the vehicle inventory of the merchant based on the query data and the transaction data, wherein if a vehicle is determined to have a high desirability value, the recommendation includes acquiring more of the vehicle and if the vehicle is determined to have a low desirability value, the recommendation includes reducing inventory of the vehicle; and transmitting, by the one or more processors, the recommendation to a graphical user interface of the merchant.

32 . The computer-implemented method of claim 31 , further comprising: determining a likelihood value, the likelihood value based on a likelihood a purchaser will purchase an available vehicle.

33 . The computer-implemented method of claim 32 , wherein the likelihood value is assigned based on a purchaser financial status associated with the purchaser, the purchaser financial status including data indicating a credit profile, including at least one of a credit score, a debt amount, a credit segmentation, or a pre-approved loan amount.

34 . The computer-implemented method of claim 31 , wherein when the recommendation includes reducing inventory of the vehicle, the recommendation includes a recommendation to offer a lower price to purchasers or performing trades with other merchants.

35 . The computer-implemented method of claim 31 , wherein the transaction data includes data indicating an available inventory of merchants in a predetermined area associated with the quantity of the one or more vehicles that were purchased or attempted to be purchased.

36 . The computer-implemented method of claim 31 , wherein determining the desirability value to each vehicle of the vehicle inventory of the merchant is based on a number of purchasable vehicles purchased in a predetermined historical period.

37 . The computer-implemented method of claim 31 , wherein determining the desirability value for each vehicle of the vehicle inventory of the merchant further includes learning relationships between demographics of purchasers.

38 . The computer-implemented method of claim 31 , wherein the one or more characteristics of the one or more vehicles includes at least one of a mileage, a total price, a monthly payment, a vehicle category, a body style, a condition, a feature, a fuel economy, a drive type, a specification, a zip code, or a selected one or more merchants of a plurality of merchants.

39 . The computer-implemented method of claim 31 , further comprising:
causing to display, via the graphical user interface, a graphical depiction of available vehicles assigned a highest desirability value below a threshold desirability value and the desirability value for the available vehicle.

40 . A system for regulating vehicle stock, the system comprising:
a memory having processor-readable instructions stored therein; and at least one processor configured to access the memory and execute the processor-readable instructions, which when executed by the at least one processor configures the at least one processor to perform a plurality of functions, including functions for:
receiving, by one or more processors, query data including one or more queries indicative of one or more characteristics of one or more vehicles;
receiving, by the one or more processors, from a database, transaction data including a quantity of the one or more vehicles that were purchased or attempted to be purchased;
monitoring, by the one or more processors, vehicle inventory of a merchant;
determining, by the one or more processors, using at least one trained machine learning model, a

Assignees

• Capital One Services Llc

Inventors

• Hoover Jason
• Ghamsari Avid
• Tang Qiaochu
• Dagley Geoffrey
• Price Micah

Classifications

• G06N3/0442

  characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] · CPC title

• G06N3/09

  Supervised learning · CPC title

• G06N3/0895

  Weakly supervised learning, e.g. semi-supervised or self-supervised learning · CPC title

• G06N3/0464

  Convolutional networks [CNN, ConvNet] · CPC title

• G06Q30/0639

  Locating goods or services, e.g. based on physical position of the goods or services within a shopping facility · CPC title