IP Library › Granted Patent US 12,614,221
Granted Patent B2
US 12,614,221 · App. 18/503,286 · Granted Apr 28, 2026

System and methods for determining enhanced counters based on integrating merchant profiles

Inventor: Walker Ramirez (Frisco, TX)
Assignee: Capital One Services, LLC
G06Q30/0631G06Q30/0283G06Q30/0641
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,614,221
App. No.
18/503,286
Granted
Apr 28, 2026
Kind
B2
Abstract

A system and method for generating enhanced counter offers is disclosed. The system and method can generate, for a merchant, a list of alternative inventory items to a given item. A plurality of historic deal metrics based on past financing terms for each of the alternative inventory items may be determined. An alternative sale price based on applying the plurality of historic deal metrics to a merchant listed sale price for the given item may be generated. A report based on the alternative sale price may be generated. The report may be transmitted to the client device for display on an interactive graphical user interface (GUI).

Claims (101)

1 . A computer implemented method comprising:

receiving, by one or more computing devices and via input fields in an interactive graphical user interface (GUI) of an application installed on a client device, offered terms including a merchant listed sale price for a given item;

performing in real-time from when the offered terms are received:

generating, by the one or more computing devices and for a merchant, a list of alternative inventory items to the given item by accessing, via an application programming interface (API) coupled to a database storing product information, and generating a similarity score between the given item and a plurality of items based on the product information;

retrieving, by the one or more computing devices and via the API, a plurality of historic deal metrics based on past financing terms for each of the alternative inventory items;

generating, by the one or more computing devices, an alternative sale price based on applying the plurality of historic deal metrics to the merchant listed sale price for the given item, wherein the alternative sale price is generated by:

identifying the merchant listed sale price,

identifying a percentage change to the merchant listed sale price,

identifying a scaling factor,

multiplying the percentage change with the merchant listed sale price and the scaling factor to obtain a first value,

adding the first value to a value of one to obtain a second value, and

multiplying the second value with the merchant listed sale price to obtain the alternative sale price;

generating, by the one or more computing devices, a report in the form of a formatted graphic listing the alternative sale price, a graphic of the given item, and product information related to the given item; and

transmitting, by the one or more computing devices and to the client device, the report for display on the interactive GUI.

2 . The method of claim 1 , further comprising filtering, by the one or more computing devices, the list of alternative inventory items prior to generating the alternative sale price to include only alternative inventory items where the plurality of historic deal metrics indicate that a difference between a final sale price and the merchant listed sale price is below a predetermined threshold value.

3 . The method of claim 1 , further comprising generating the percentage change to the merchant listed sale price based on:

identifying, by the one or more computing devices, an average percent change in sale price for the merchant;

identifying, by the one or more computing devices, a standard deviation for the average percent change in sale price for the merchant;

identifying, by the one or more computing devices, a counter offer for the given item;

multiplying, by the one or more computing devices, a constant with the standard deviation to obtain a third value;

subtracting, by the one or more computing devices, the third value from the average percent change in sale price to obtain a fourth value;

dividing, by the one or more computing devices, the counter offer for the given item by the merchant listed sale price for the given item to obtain a fifth value;

determining, by the one or more computing devices, which of the fourth value or the fifth value is greater; and

setting, by the one or more computing devices, the percentage change to the merchant listed sale price as the determined greater value.

4 . The method of claim 1 , further comprising generating the scaling factor based on:

identifying, by the one or more computing devices, a maximum counter intensity value;

identifying, by the one or more computing devices, a counter offer for the given item;

identifying, by the one or more computing devices, a size of a counter band;

dividing, by the one or more computing devices, an absolute value of the counter offer for the given item by the size of the counter band to obtain a sixth value;

determining a floor of the sixth value to obtain an integer seventh value;

determining, by the one or more computing devices, which of the seventh value or the maximum counter intensity value is smaller; and

dividing the smaller value by the maximum counter intensity value to obtain the scaling factor.

5 . The method of claim 1 , wherein the method is implemented on devices of a cloud-computing environment.

6 . A non-transitory computer readable medium including instructions that when executed by one or more processors of a computing system, cause the computing system to perform operations comprising:

receiving, via input fields in an interactive graphical user interface (GUI) of an application installed on a client device, offered terms including a merchant listed sale price for a given item;

performing in real-time from when the offered terms are received:

generating, for a merchant, a list of alternative inventory items to the given item by accessing, via an application programming interface (API) coupled to a database storing product information, and generating a similarity score between the given item and a plurality of items based on the product information;

retrieving, via the API, a plurality of historic deal metrics based on past financing terms for each of the alternative inventory items;

generating an alternative sale price based on applying the plurality of historic deal metrics to the merchant listed sale price for the given item, wherein the alternative sale price is generated by:

identifying the merchant listed sale price,

identifying a percentage change to the merchant listed sale price,

identifying a scaling factor,

multiplying the percentage change with the merchant listed sale price and the scaling factor to obtain a first value,

adding the first value to a value of one to obtain a second value, and

multiplying the second value with the merchant listed sale price to obtain the alternative sale price;

generating a report in the form of a formatted graphic listing the alternative sale price, a graphic of the given item, and product information related to the given item; and

transmitting, by the one or more computing devices and to the client device, the report for display on the interactive GUI.

7 . The non-transitory computer readable medium of claim 6 , wherein the operations further comprise filtering the list of alternative inventory items prior to generating the alternative sale price to include only alternative inventory items where the plurality of historic deal metrics indicate that a difference between a final sale price and the merchant listed sale price is below a predetermined threshold value.

8 . The non-transitory computer readable medium of claim 6 , wherein the operations further comprise generating the percentage change to the merchant listed sale price based on:

identifying an average percent change in sale price for the merchant;

identifying a standard deviation for the average percent change in sale price for the merchant;

identifying, by the one or more computing devices, a counter offer for the given item;

multiplying a constant with the standard deviation to obtain a third value;

subtracting the third value from the average percent change in sale price to obtain a fourth value;

dividing the counter offer for the given item by the merchant listed sale price for the given item to obtain a fifth value;

determining which of the fourth value or the fifth value is greater; and

setting the percentage change to the merchant listed sale price as the determined greater value.

9 . The non-transitory computer readable medium of claim 6 , wherein the operations further comprise generating the scaling factor based on:

identifying a maximum counter intensity value;

identifying a counter offer for the given item;

identifying a size of a counter band;

dividing an absolute value of the counter offer for the given item by the size of the counter band to obtain a sixth value;

determining which of the sixth value or the maximum counter intensity value is smaller;

determining a floor of the sixth value to obtain an integer seventh value; and

dividing the smaller value by the maximum counter intensity value to obtain the scaling factor.

10 . The non-transitory computer readable medium of claim 6 , wherein the non-transitory computer readable medium is implemented on devices of a cloud-computing environment.

11 . A computing system comprising:

a memory storing instructions;

a processor coupled to the memory and configured to process the stored instructions to perform operations comprising:

receive, via input fields in an interactive graphical user interface (GUI) of an application installed on a client device, offered terms including a merchant listed sale price for a given item;

generate, for a merchant, a list of alternative inventory items to the given item by accessing, via an application programming interface (API) coupled to a database storing product information, and generating a similarity score between the given item and a plurality of items based on the product information;

retrieve, via the API, a plurality of historic deal metrics based on past financing terms for each of the alternative inventory items;

generate an alternative sale price based on applying the plurality of historic deal metrics to the merchant listed sale price for the given item, wherein the alternative sale price is generated by:

identifying the merchant listed sale price,

identifying a percentage change to the merchant listed sale price,

identifying a scaling factor,

multiplying the percentage change with the merchant listed sale price and the scaling factor to obtain a first value,

adding the first value to a value of one to obtain a second value, and

multiplying the second value with the merchant listed sale price to obtain the alternative sale price;

generate a report in the form of a formatted graphic listing the alternative sale price, a graphic of the given item, and product information related to the given item; and

a communication unit including microelectronics, coupled to the processor, configured to:

transmit, to the client device, the report for display on the interactive GUI.

12 . The computing system of claim 11 , wherein the control unitprocessor is further configured to filter the list of alternative inventory items prior to generating the alternative sale price to include only alternative inventory items where the plurality of historic deal metrics indicate that a difference between a final sale price and the merchant listed sale price is below a predetermined threshold value.

13 . The computing system of claim 11 , wherein the processor is further configured to generate the percentage change to the merchant listed sale price based on:

identifying an average percent change in sale price for the merchant;

identifying a standard deviation for the average percent change in sale price for the merchant;

identifying a counter offer for the given item;

multiplying a constant with the standard deviation to obtain a third value;

subtracting the third value from the average percent change in sale price to obtain a fourth value;

dividing the counter offer for the given item by the merchant listed sale price for the given item to obtain a fifth value;

determining which of the fourth value or the fifth value is greater; and

setting the percentage change to the merchant listed sale price as the determined greater value.

14 . The computing system of claim 11 , wherein the processor is further configured to generate the scaling factor based on:

identifying a maximum counter intensity value;

identifying a counter offer for the given item;

identifying a size of a counter band;

dividing an absolute value of the counter offer for the given item by the size of the counter band to obtain a sixth value;

determining a floor of the sixth value to obtain a seventh value;

determining which of the seventh value or the maximum counter intensity value is smaller; and

dividing the determined smaller value by the maximum counter intensity value to obtain the scaling factor.

15 . The computing system of claim 11 , wherein the computing system is implemented on devices of a cloud-computing environment.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 7, 2023
From: RAMIREZ, WALKER
To: CAPITAL ONE SERVICES, LLC
Reel/Frame 065479/0001 →
Continuity (1)
Related Publication 20250148520A1 · May 8, 2025
References Cited (13)
US 5774883A · Andersen et al. · 1998 [cited by applicant]
US 7908210B2 · Huber et al. · 2011 [cited by applicant]
US 8560438B2 · Hankey et al. · 2013 [cited by applicant]
US 10387951B2 · Scopazzi · 2019 [cited by applicant]
US 10438256B2 · Wollmer et al. · 2019 [cited by applicant]
US 20100088238A1 · Butterfield · 2010 [cited by examiner]
US 20150120489A1 · Edelman · 2015 [cited by applicant]
US 20170161825A1 · Nair · 2017 [cited by examiner]
US 20190139134A1 · Wickett · 2019 [cited by applicant]
US 20190295143A1 · Ng · 2019 [cited by examiner]
US 20190362374A1 · Mungoli · 2019 [cited by examiner]
US 20210027317A1 · Baghestani et al. · 2021 [cited by applicant]
Yanbin, Peng, and Zheng Zhijun. “Automated Negotiation Based on Ensemble Learning and Optimal Counter Proposal.” [cited by examiner]