IP Library › Granted Patent US 11,657,445
Granted Patent B2
US 11,657,445 · App. 17/378,833 · Granted May 23, 2023

System, method, and medium for obtaining user parameters of e-commerce users to auto complete checkout forms

Inventors: Austin Walters (McLean, VA); Fardin Abdi Taghi Abad (McLean, VA); Jeremy Goodsitt (McLean, VA)
Assignee: Capital One Services, LLC
G06Q30/0641G06F40/174G06N20/00G06Q30/0635H04L67/535
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Quick Facts
Patent No.
US 11,657,445
App. No.
17/378,833
Granted
May 23, 2023
Kind
B2
Abstract

A system for obtaining user parameters of e-commerce users to auto complete checkout forms includes one or more processors configured to monitor user interactions of a user with a merchant website on a user device; determine an intent to purchase one or more items based of the monitoring; determine an unfilled template of a checkout form associated with the merchant website based on previously stored website information, wherein the unfilled template of the checkout form comprises a plurality of checkout form fields; determine one or more user parameters associated with the user device; apply a machine learning algorithm to predict a geolocation of the user device based on the one or more user parameters; and auto fill the at least one of the plurality of checkout form fields in the unfilled template of the checkout form based on the predicted geolocation.

Claims (46)

1. A system for auto completing checkout forms, the system comprising:

one or more memory devices storing instructions; and

one or more processors configured to execute the instructions to:

identify, based on interactions of a user device with a merchant website and on previously stored website information, an unfilled template of a checkout form associated with the merchant website, wherein the unfilled template of the checkout form comprises a plurality of checkout form fields;

determine a geolocation of the user device based on an Internet Protocol address of the user device;

provide the geolocation to a machine learning algorithm, wherein the machine learning algorithm is trained to identify an autofill recommendation for a checkout form field of the plurality of checkout form fields;

receiving, from the machine learning algorithm, the autofill recommendation, wherein the autofill recommendation is generated by the machine learning algorithm based on the geolocation provided to the machine learning algorithm;

assign an accuracy score to the autofill recommendation based on a comparison of the autofill recommendation with information manually populated in another of the plurality of checkout form fields of the checkout form; and

in response to determining that the accuracy score satisfies a threshold, provide the autofill recommendation to the user device.

2. The system of claim 1 , wherein the one or more processors are further configured to determine an intent to purchase one or more items based on monitoring user interactions of a user with the merchant website on the user device.

3. The system of claim 2 , wherein the intent to purchase the one or more items includes adding the one or more items in a shopping cart of the merchant website.

4. The system of claim 1 , wherein the one or more processors are further configured to include one or more form fields of the plurality of checkout form fields in a first list stored in a database, in response to determining that the accuracy score associated with the one or more form fields of the plurality of checkout form fields does not exceed a first threshold value.

5. The system of claim 4 , wherein the one or more processors are further configured to store the unfilled template of the checkout form including the autofill recommendation of the one or more form fields of the plurality of checkout form fields in the database.

6. The system of claim 1 , wherein the one or more processors are configured to include the autofill recommendation of one or more form fields of the plurality of checkout form fields to update the unfilled template of the checkout form, in response to determining that the accuracy score associated with the one or more form fields of the plurality of checkout form fields exceeds a second threshold value.

7. The system of claim 1 , wherein determining the geolocation of the user device further comprises:

determining the Internet Protocol address of the user device; and

identifying, based on the Internet Protocol address of the user device, a routing device through which the interactions were routed by performing a reverse lookup of the Internet Protocol address of the user device.

8. A method for auto completing checkout forms, the method comprising:

identifying, based on interactions of a user device with a merchant interface, an unfilled template of a checkout form associated with the merchant interface, wherein the unfilled template of the checkout form comprises a plurality of input fields;

determining a geolocation of the user device based on an Internet Protocol address of the user device;

providing the geolocation to a machine learning algorithm, wherein the machine learning algorithm is trained to identify an autofill recommendation for an input field of the plurality of input fields;

receiving, from the machine learning algorithm, the autofill recommendation, wherein the autofill recommendation is generated by the machine learning algorithm based on the geolocation provided to the machine learning algorithm;

assigning an accuracy score to the autofill recommendation based on a comparison of the autofill recommendation with information manually populated in another of the plurality of input fields of the checkout form; and

in response to determining that the accuracy score satisfies a threshold, providing the autofill recommendation to the user device.

9. The method of claim 8 , further comprising determining an intent to purchase one or more items based on monitoring user interactions of a user with the merchant interface of a merchant website.

10. The method of claim 9 , wherein the intent to purchase the one or more items includes adding the one or more items in a shopping cart of the merchant website.

11. The method of claim 8 , further comprising including one or more input fields of the plurality of input fields in a first list stored in a database, in response to determining that the accuracy score associated with each of the one or more input fields of the plurality of input fields does not exceed a first threshold value.

12. The method of claim 11 , further comprising storing the unfilled template of the checkout form including the autofill recommendation of the one or more input fields of the plurality of input fields in the database.

13. The method of claim 8 , further comprising including the autofill recommendation of one or more input fields of the plurality of input fields to update the unfilled template of the checkout form, in response to determining that the accuracy score associated with the one or more input fields of the plurality of input fields exceeds a second threshold value.

14. The method of claim 8 , wherein determining the geolocation of the user device further comprises:

determining the Internet Protocol address of the user device; and

identifying, based on the Internet Protocol address of the user device, a routing device through which the interactions were routed by performing a reverse lookup of the Internet Protocol address of the user device.

15. A non-transitory, computer-readable medium for auto completing checkout forms, storing instructions that, when executed by one or more processors, cause operations comprising:

identifying, based on interactions of a user device with a merchant interface, an unfilled template of a checkout form associated with the merchant interface, wherein the unfilled template of the checkout form comprises a plurality of input fields;

determining a geolocation of the user device based on an Internet Protocol address of the user device;

providing the geolocation to a machine learning algorithm, wherein the machine learning algorithm is trained to identify an autofill recommendation for an input field of the plurality of input fields;

receiving, from the machine learning algorithm, the autofill recommendation, wherein the autofill recommendation is generated by the machine learning algorithm based on the geolocation;

assigning an accuracy score to the autofill recommendation based on a comparison of the autofill recommendation with information manually populated in another of the plurality of input fields; and

in response to determining that the accuracy score satisfies a threshold, providing the autofill recommendation to the user device.

16. The non-transitory, computer-readable medium of claim 15 , further storing instructions that cause the one or more processors to determine an intent to purchase one or more items based on monitoring user interactions of a user with the merchant interface.

17. The non-transitory, computer-readable medium of claim 16 , wherein the intent to purchase the one or more items includes adding the one or more items in a shopping cart of a website associated with the merchant interface.

18. The non-transitory, computer-readable medium of claim 15 , further storing instructions that cause the one or more processors to include one or more input fields of the plurality of input fields in a first list stored in a database, in response to determining that the accuracy score associated with the one or more input fields of the plurality of input fields does not exceed a first threshold value.

19. The non-transitory, computer-readable medium of claim 15 , further storing instructions that cause the one or more processors to include the autofill recommendation of one or more input fields of the plurality of input fields to update the unfilled template of the checkout form, in response to determining that the accuracy score associated with the one or more input fields of the plurality of input fields exceeds a second threshold value.

20. The non-transitory, computer-readable medium of claim 15 , wherein the instructions for determining the geolocation of the user device further cause the one or more processors to:

determine the Internet Protocol address of the user device; and

identify, based on the Internet Protocol address of the user device, a routing device through which the interactions were routed by performing a reverse lookup of the Internet Protocol address of the user device.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 9, 2023
From: WALTERS, AUSTIN; ABAD, FARDIN ABDI TAGHI; GOODSITT, JEREMY
To: CAPITAL ONE SERVICES, LLC
Reel/Frame 062314/0375 →
Continuity (2)
Continuation 16591744 · Oct 3, 2019
Related Publication 20210342923A1 · Nov 4, 2021