IP Library Granted Patent US 12,205,134
Granted Patent B2
US 12,205,134 · App. 18/196,802 · Granted Jan 21, 2025

Systems and methods for autonomous management of manufacturer coupons

Inventors: Adam Robert Snopek (Chicago, IL); Renata Lurye (Glenview, IL); Oliver Derza (Willowbrook, IL)
Assignee: WALGREEN CO.
G06Q30/0232G06F16/951G06Q30/0224G06Q30/0238G16H20/10
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 12,205,134
App. No.
18/196,802
Granted
Jan 21, 2025
Kind
B2
Abstract

Methods and systems may support dynamic, real-time or near-real-time processing, analysis, and processing of data to automatically identify and obtain coupons corresponding to consumer products such that, in response to receiving a request to purchase one or more products, qualifying coupons may be automatically identified, retrieved, and applied to the purchase.

Claims (34)

1. A computing system:

one or more processors; and

one or more computer memories storing non-transitory computer-executable instructions that, when executed via the one or more processors, cause the computing system to:

transmit a request for a server to generate and provide one or more available coupons as a portable document format (PDF) file or webpage representing the one or more available coupons;

obtain the generated PDF or webpage from the third-party server;

extract relevant coupon data for the one or more available coupons from the obtained PDF or webpage at least by (1) identifying an electronic file format of the obtained PDF or webpage, (2) standardizing or resizing the downloaded PDF or webpage based upon a pixel width of the downloaded PDF or webpage, (3) determining a pixel location of a bounding box containing the relevant coupon data within the standardized or resized PDF or webpage, and (4) applying an optical character recognition technique within the determined bounding box to identify text corresponding to the relevant coupon data; and

using the extracted relevant coupon data, apply the one or more available coupons in relation to a purchase of one or more products.

2. The computing system of claim 1 , wherein the one or more products comprise one or more prescription medications.

3. The computing system of claim 1 , wherein the non-transitory computer-executable instructions, when executed via the one or more processors, further cause the computing system to analyze a request from a user to purchase the one or more products, to determine whether the request qualifies for the one or more available coupons.

4. The computing system of claim 3 , wherein determining whether the request qualifies for the one or more available coupons includes determining whether a user requesting to purchase the one or more products satisfies one or more criteria.

5. The computing system of claim 3 , wherein the non-transitory computer-executable instructions, when executed via the one or more processors, further cause the computing system to update the request to purchase the one or more products after applying the one or more available coupons in order to adjust a price of the one or more products.

6. The computing system of claim 1 , further comprising a clock component configured to define a frequency with which the computing system communicates with the server to identify available coupons.

7. The computing system of claim 1 , wherein the relevant coupon data comprises a barcode.

8. A computer-implemented method implemented via one or more processors, the method comprising:

transmitting a request for a server to generate and provide one or more available coupons as a portable document format (PDF) file or webpage representing the one or more available coupons;

obtaining the generated PDF or webpage from the third-party server;

extracting relevant coupon data for the one or more available coupons from the obtained PDF or webpage at least by (1) identifying an electronic file format of the obtained PDF or webpage, (2) standardizing or resizing the downloaded PDF or webpage based upon a pixel width of the downloaded PDF or webpage, (3) determining a pixel location of a bounding box containing the relevant coupon data within the standardized or resized PDF or webpage, and (4) applying an optical character recognition technique within the determined bounding box to identify text corresponding to the relevant coupon data; and

using the extracted relevant coupon data, applying the one or more available coupons in relation to a purchase of one or more products.

9. The computer-implemented method of claim 8 , wherein the one or more products comprise one or more prescription medications.

10. The computer-implemented method of claim 8 , further comprising analyzing a request from a user to purchase the one or more products, to determine whether the request qualifies for the one or more available coupon.

11. The computer-implemented method of claim 10 , wherein determining whether the request qualifies for the one or more available coupons includes determining whether a user requesting to purchase the one or more products satisfies one or more criteria.

12. The computer-implemented method of claim 10 , further comprising updating the request to purchase the one or more products after applying the one or more available coupons in order to adjust a price of the one or more products.

13. The computer-implemented method of claim 8 , comprising communicating with the server at pre-determined time intervals based upon a frequency defined by a clock component.

14. The computer-implemented method of claim 8 , wherein the relevant coupon data comprises a barcode.

15. One or more non-transitory computer-readable media storing non-transitory computer-executable instructions that, when executed via one or more processors of one or more computers, cause the one or more computers to:

transmit a request for a server to generate and provide one or more available coupons as a portable document format (PDF) file or webpage representing the one or more available coupons;

obtain the generated PDF or webpage from the third-party server;

extract relevant coupon data for the one or more available coupons from the obtained PDF or webpage at least by (1) identifying an electronic file format of the obtained PDF or webpage, (2) standardizing or resizing the downloaded PDF or webpage based upon a pixel width of the downloaded PDF or webpage, (3) determining a pixel location of a bounding box containing the relevant coupon data within the standardized or resized PDF or webpage, and (4) applying an optical character recognition technique within the determined bounding box to identify text corresponding to the relevant coupon data; and

using the extracted relevant coupon data, apply the one or more available coupons in relation to a purchase of one or more products.

16. The one or more non-transitory computer-readable media of claim 15 , wherein the one or more products comprise one or more prescription medications.

17. The one or more non-transitory computer-readable media of claim 15 , wherein the non-transitory computer-executable instructions, when executed via the one or more processors, further cause the one or more computers to analyze a request from a user to purchase the one or more products, to determine whether the request qualifies for the one or more available coupons.

18. The one or more non-transitory computer-readable media of claim 17 , wherein determining whether the request qualifies for the one or more available coupons includes determining whether a user requesting to purchase the one or more products satisfies one or more criteria.

19. The one or more non-transitory computer-readable media of claim 17 , wherein the non-transitory computer-executable instructions, when executed via the one or more processors, further cause the one or more computers to update the request to purchase the one or more products after applying the one or more available coupons in order to adjust a price of the one or more products.

20. The one or more non-transitory computer-readable media of claim 15 , wherein the non-transitory computer-executable instructions, when executed via the one or more processors, further cause the one or more computers to utilize a clock component to communicate with the server at pre-determined time intervals based upon a frequency defined by the clock component.

Assignments (3)
INTELLECTUAL PROPERTY SECURITY AGREEMENT Recorded Aug 28, 2025
From: WALGREEN CO.
To: SIXTH STREET LENDING PARTNERS, AS COLLATERAL AGENT
Reel/Frame 072606/0878 →
SECURITY INTEREST Recorded Aug 28, 2025
From: WALGREEN CO.; DUANE READE; WALGREENS SPECIALTY PHARMACY LLC; WALGREENS BOOTS ALLIANCE, INC.
To: WELLS FARGO BANK, NATIONAL ASSOCIATION, AS COLLATERAL AGENT
Reel/Frame 072679/0926 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 16, 2023
From: SNOPEK, ADAM ROBERT; LURYE, RENATA; DERZA, OLIVER
To: WALGREEN CO.
Reel/Frame 063657/0234 →
Continuity (2)
Continuation 16596179 · Oct 8, 2019
Related Publication 20230281654A1 · Sep 7, 2023
References Cited (17)
US 20040030598A1 · Boal · 2004 [cited by examiner]
US 20040125755A1 · Roberts · 2004 [cited by applicant]
US 20080205850A1 · Collins · 2008 [cited by examiner]
US 20090283589A1 · Moore · 2009 [cited by examiner]
US 20110106605A1 · Malik · 2011 [cited by examiner]
US 20120136712A1 · Chang · 2012 [cited by examiner]
US 20130290172A1 · Mashinsky · 2013 [cited by examiner]
US 20160300256A1 · Nagarajan · 2016 [cited by examiner]
US 20190214116A1 · Eberting · 2019 [cited by examiner]
Y. Wan and G. Peng, “What's Next for Shopbots?,” in Computer, vol. 43, No. 5, pp. 20-26, May 2010, doi: 10.1109/MC.2010.93. (Year: 2010). [cited by examiner]
Removable Anti-coupon Bar code for Confirming Consumer Attention An IP.com Prior Art Database Technical Disclosure Authors et. al.: Disclosed Anonymously IP.com No. IPCOM000197125D IP.com Electronic Publication Date: Ju… [cited by examiner]
Y. Wan and G. Peng, “What's Next for Shopbots?,” in Computer, vol. 43, No. 5, pp. 20-26, May 2010, doi: 10.1109/MC.2010.93. (Year: 2010) (Year: 2010). [cited by examiner]
M. Chevalier, J. Mothe and P. Terrier, “Tags and Information Recollection,” 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Naples, Italy, 2016, pp. 373-380, doi: 10.1109/… [cited by examiner]
Chevalier et al., “Tags and Information Recollection,” 2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), Naples, Italy, 2016, pp. 373-380, doi: 10.1109/SITIS.2016.66. (Year:… [cited by applicant]
Wan et al., “What's Next for Shopbots?,” in Computer, vol. 43, No. 5, pp. 20-26, May 2010, doi: 10.1109/MC.2010.93. (Year: 2010). [cited by applicant]
Paulson et al., “Scanning the Future with New Barcodes,” in Computer, vol. 44, No. 1, pp. 20-23, Jan. 2011, doi: 10.1109/MC.2011.25. (Year: 2011). [cited by applicant]
Javkar et al., “Best offer recommendation service,” 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2016, pp. 2430-2436, doi: 10.1109/ICACCI.2016.7732421. (Year: 2016). [cited by applicant]