IP Library Granted Patent US 12,154,047
Granted Patent B1
US 12,154,047 · App. 17/807,651 · Granted Nov 26, 2024

System for electronic service interoperability

Inventors: Rajeswaran Govindan (Livermore, CA); Margaret Seter Honeycutt (Crockett, CA); Wyman Yu (San Francisco, CA); Jason V. Biala (Martinez, CA); Ryan Lee Hammond (San Jose, CA); Dennis E. Montenegro (Concord, CA); Christopher Sipanya (San Jose, CA); Sergey Yamandiy (Castro Valley, CA); Miriam Felecia Clark (San Francisco, CA); Jason Huang (San Francisco, CA)
Assignee: Wells Fargo Bank, N.A.
G06Q10/06311G06Q10/06316G06Q30/0601H04L67/306
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Quick Facts
Patent No.
US 12,154,047
App. No.
17/807,651
Granted
Nov 26, 2024
Kind
B1
Abstract

A method may include receiving, at a server device, a request from a third-party website over an application programming interface (API), the request including a user identification and an item identification; retrieving, at the server device, a set of goal data structures generated for a user profile of a user matching the user identification; matching, at the server device, the item identification to an identification within a goal data structure of the set of goal data structures, the goal data structure including a plurality of steps associated with the goal data structure; generating, at the server device, a response data structure including a status of each step of the plurality of steps associated with the goal data structure; and transmitting the response data structure to the third-party website.

Claims (67)

1. A method comprising:

receiving, at a server device, a request from a third-party merchant website over an application programming interface (API), the request including a user identification and an item identification of an item for purchase on the third-party merchant website, the item identification associated with an item in a shopping cart on the third-party merchant website;

retrieving, at the server device, a set of item purchase goal data structures generated for a user profile of a user matching the user identification;

matching, at the server device, the item identification of the item for purchase to an item identification within an item purchase goal data structure of the set of item purchase goal data structures, the item purchase goal data structure including a plurality of steps associated with the item purchase goal data structure and a uniform resource locator of the third-party merchant website;

determining a status of a research step of the plurality of steps by:

inputting categorizations of a browser history associated with the user identification into a trained machine learning model;

receiving an output from the trained machine learning model identifying a confidence level above a threshold value indicating the item was researched; and

based on the confidence level being above the threshold, updating the status of the research step as completed;

generating, at the server device, a response data structure including a shopping cart embedded user interface with a graphical representation of a status of each step of the plurality of steps associated with the item purchase goal data structure; and

transmitting the response data structure to the third-party merchant website.

2. The method of claim 1 , wherein generating, at the server device, the response data structure includes generating the shopping cart embedded user interface, the shopping cart embedded user interface including:

a number of unfilled graphical objects representing uncompleted steps of the plurality of steps associated with the item purchase goal data structure; and

a number of filled graphical objects representing completed steps of the plurality of steps associated with the item purchase goal data structure.

3. The method of claim 1 , further comprising:

receiving, at the server device, data indicating a change in status of a step in the plurality of steps; and

updating the item purchase goal data structure based on the change in status.

4. The method of claim 3 , wherein the data indicating the change in status is based on location data from a mobile device, the mobile device identified as associated with the user in the user profile.

5. The method of claim 3 , wherein the data indicating the change in status is based on a length of time.

6. The method of claim 3 , wherein the data indicating the change in status is based on receiving an affirmation from the user that the step has been completed.

7. The method of claim 3 , further comprising:

selecting a plurality of users from a list of users stored in the user profile;

for each respective user in the plurality of users, transmitting a request message to a computing device of the respective user, the request message including an approval option and a disapproval option; and

wherein the data indicating the change in status is based on respective responses to the request message from each respective user.

8. A non-transitory computer-readable medium comprising instructions, which when executed by at least one processor, configure the at least one processor to perform operations comprising:

receiving, at a server device, a request from a third-party merchant website over an application programming interface (API), the request including a user identification and an item identification of an item for purchase on the third-party merchant website, the item identification associated with an item in a shopping cart on the third-party merchant website;

retrieving, at the server device, a set of item purchase goal data structures generated for a user profile of a user matching the user identification;

matching, at the server device, the item identification of the item for purchase to an item identification within an item goal data structure of the set of item purchase goal data structures, the item purchase goal data structure including a plurality of steps associated with the item purchase goal data structure and a uniform resource locator of the third-party merchant website;

determining a status of a research step of the plurality of steps by:

inputting categorizations of a browser history associated with the user identification into a trained machine learning model;

receiving an output from the trained machine learning model identifying a confidence level above a threshold value indicating the item was researched; and

based on the confidence level being above the threshold, updating the status of the research step as completed;

generating, at the server device, a response data structure including a shopping cart embedded user interface with a graphical representation of a status of each step of the plurality of steps associated with the item purchase goal data structure; and

transmitting the response data structure to the third-party merchant website.

9. The non-transitory computer-readable medium of claim 8 , wherein the operation of generating, at the server device, the response data structure includes generating the shopping cart embedded user interface, the shopping cart embedded user interface including:

a number of unfilled graphical objects representing uncompleted steps of the plurality of steps associated with the item purchase goal data structure; and

a number of filled graphical objects representing completed steps of the plurality of steps associated with the item purchase goal data structure.

10. The non-transitory computer-readable medium of claim 8 , further comprising instructions, which when executed by the at least one processor, configure the at least one processor to perform operations comprising:

receiving, at the server device, data indicating a change in status of a step in the plurality of steps; and

updating the item purchase goal data structure based on the change in status.

11. The non-transitory computer-readable medium of claim 10 , wherein the data indicating the change in status is based on location data from a mobile device, the mobile device identified as associated with the user in the user profile.

12. The non-transitory computer-readable medium of claim 10 , wherein the data indicating the change in status is based on a length of time.

13. The non-transitory computer-readable medium of claim 10 , wherein the data indicating the change in status is based on receiving an affirmation from the user that the step has been completed.

14. The non-transitory computer-readable medium of claim 10 , further comprising instructions, which when executed by the at least one processor, configure the at least one processor to perform operations comprising:

selecting a plurality of users from a list of users stored in the user profile;

for each respective user in the plurality of users, transmitting a request message to a computing device of the respective user, the request message including an approval option and a disapproval option; and

wherein the data indicating the change in status is based on respective responses to the request message from each respective user.

15. A system comprising:

at least one processor; and

a storage device comprising instructions, which when executed by the at least one processor, configure the at least one processor to perform operations comprising:

receiving, at a server device, a request from a third-party merchant website over an application programming interface (API), the request including a user identification and an item identification of an item for purchase on the third-party merchant website, the item identification associated with an item in a shopping cart on the third-party merchant website;

retrieving, at the server device, a set of item purchase goal data structures generated for a user profile of a user matching the user identification;

matching, at the server device, the item identification of the item for purchase to an identification within an item purchase goal data structure of the set of goal data structures, the item purchase goal data structure including a plurality of steps associated with the item purchase goal data structure and a uniform resource locator of the third-party merchant website;

determining a status of a research step of the plurality of steps by:

inputting categorizations of a browser history associated with the user identification into a trained machine learning model;

receiving an output from the trained machine learning model identifying a confidence level above a threshold value indicating the item was researched; and

based on the confidence level being above the threshold, updating the status of the research step as completed;

generating, at the server device, a response data structure including a shopping cart embedded user interface with a graphical representation of a status of each step of the plurality of steps associated with the goal data structure; and

transmitting the response data structure to the third-party merchant website.

16. The system of claim 15 , wherein the operation of generating, at the server device, the response data structure includes generating the shopping cart embedded user interface, the shopping cart embedded user interface including:

a number of unfilled graphical objects representing uncompleted steps of the plurality of steps associated with the item purchase goal data structure; and

a number of filled graphical objects representing completed steps of the plurality of steps associated with the item purchase goal data structure.

17. The system of claim 15 , the storage device further comprising instructions, which when executed by the at least one processor, configure the at least one processor to perform operations comprising:

receiving, at the server device, data indicating a change in status of a step in the plurality of steps; and

updating the item purchase goal data structure based on the change in status.

18. The system of claim 17 , wherein the data indicating the change in status is based on location data from a mobile device, the mobile device identified as associated with the user in the user profile.

19. The system of claim 17 , wherein the data indicating the change in status is based on a length of time.

20. The system of claim 17 , wherein the data indicating the change in status is based on receiving an affirmation from the user that the step has been completed.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 19, 2022
From: GOVINDAN, RAJESWARAN; HONEYCUTT, MARGARET SETER; YU, WYMAN; BIALA, JASON V; HAMMOND, RYAN LEE; MONTENEGRO, DENNIS E; SIPANYA, CHRISTOPHER; YAMANDIY, SERGEY; CLARK, MIRIAM FELECIA; HUANG, JASON
To: WELLS FARGO BANK, N.A.
Reel/Frame 061141/0581 →
Cited By (7)
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