IP Library Granted Patent US 12,373,781
Granted Patent B1
US 12,373,781 · App. 18/314,014 · Granted Jul 29, 2025

Intelligent image recommendations

Inventors: Matthew Capers (San Francisco, CA); Marsal Gavalda (Sandy Springs, GA); Roshan Jhunja (Scarsdale, NY)
Assignee: Block, Inc.
G06Q10/087G06Q20/202G06Q20/203G06Q30/0631G06Q30/0641
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 12,373,781
App. No.
18/314,014
Granted
Jul 29, 2025
Kind
B1
Abstract

Techniques for obtaining images that are representative of items of inventory are described herein. A service provider may receive transaction data from a plurality of merchants and access visual representation data associated with items in the inventory of the plurality of merchants. The service provider may receive from a merchant an indication of intent to add an item of inventory. A data model is trained that uses the transaction data and the visual representation data. Merchant-facing and customer-facing visual representations for the item are obtained using the data model. An approval user interface is displayed for the merchant to approve use of the visual representations. Based on receiving approval, the merchant-facing image is presented via a merchant-facing user interface and the customer-facing image is presented via a customer-facing user interface.

Claims (77)

1. A system comprising:

one or more processors; and

one or more computer-readable media storing instructions executable by the one or more processors, wherein the instructions program the one or more processors to:

receive, by one or more servers of a service provider and from point-of-sale (POS) devices of a plurality of merchants, transaction data associated with transactions of the plurality of merchants and associated with a plurality of items, wherein the transaction data includes, for an individual transaction of the transactions, an indication of a corresponding merchant, of the plurality of merchants, conducting the individual transaction and an indication of one or more items purchased in the individual transaction, wherein the indication of the one or more items includes corresponding descriptors and visual representations of the one or more items;

access, by the one or more servers, visual representation data associated with a plurality of visual representations corresponding to items, of the plurality of items, that are in inventories of the plurality of merchants;

receive, by the one or more servers and from a POS device, of the POS devices, of a merchant of the plurality of merchants, an indication of intent to add a new item to an inventory associated with the merchant, the indication including one or more descriptors of the new item;

train, by the one or more servers, a data model to output one or more visual representations of an item based on respective descriptors of the item and using at least the transaction data and image data associated with the plurality of items, wherein training data includes efficacy data of previous associations between individual visual representations and corresponding individual items of the plurality of items;

based at least in part on the indication of intent to add the new item, input, by the one or more servers, the one or more descriptors of the new item into the data model;

receive by the one or more servers and from the data model, a merchant-facing visual representation and a customer-facing visual representation for representing the new item, wherein the customer-facing visual representation is selected based on first efficacy data associated with the customer-facing visual representation being associated with a higher conversion rate than second efficacy data associated with the merchant-facing visual representation;

cause presentation, by the one or more servers and via a display of the at least one of the POS device or another merchant device, an approval user interface including a merchant-facing image based at least in part on the merchant-facing visual representation and a customer-facing image based at least in part on the customer-facing visual representation and a request for approval to use the merchant-facing image and the customer-facing image for representing the new item; and

based at least in part on receiving the approval to use the merchant-facing image and the customer-facing image, cause, by the one or more servers, the merchant-facing image to be presented via a merchant-facing user interface and the customer-facing image to be presented via a customer-facing user interface.

2. The system of claim 1 , wherein the indication of intent to add the new item to the inventory associated with the merchant comprises input by the merchant, via an inventory user interface, wherein the inventory user interface is associated with building a catalog of inventory, the input comprising at least one of:

a description of the new item;

an inventory code associated with the new item; or

a manufacturer associated with the new item.

3. The system of claim 1 , wherein at least one of:

the merchant-facing image is of a first quality and the customer-facing image is of a second quality, the second quality being greater than the first quality; or

the merchant-facing visual representation is of a third quality and the customer-facing visual representation is of a fourth quality, the fourth quality being greater than the third quality.

4. The system of claim 1 , wherein the instructions further program the one or more processors to:

analyze, by the one or more servers, one or more websites displaying visual representations; and

compare, by the one or more servers, the visual representations with a description associated with the new item, the description provided by the merchant in the indication of intent to add the new item,

wherein obtaining the merchant-facing visual representation and the customer-facing visual representation is further based at least in part on comparing visual representations images with the description.

5. The system of claim 1 , wherein the instructions further program the one or more processors to:

verify, by the one or more servers, that a first license associated with the merchant-facing visual representation and a second license associated with the customer-facing visual representation are appropriate for use by the merchant.

6. The system of claim 1 , wherein the instructions further program the one or more processors to:

identify, by the one or more servers, at least one of a first license associated with the merchant-facing visual representation or a second license associated with the customer-facing visual representation; and

determine, by the one or more servers, that the at least one of the first license or the second license is issued to a public domain,

wherein the request for approval is based at least in part on the at least one of the first license or the second license being issued to the public domain.

7. The system of claim 1 , wherein the plurality of merchants receives inventory services from the service provider.

8. The system of claim 1 , wherein the plurality of merchants can access the visual representation data via respective instances of a point-of-sale (POS) application executable by the POS devices, and wherein an instance of the POS application configures a device to process transactions via the service provider on behalf of the merchant.

9. The system of claim 1 , wherein the new item comprises a first item, wherein the merchant comprises a first merchant, and wherein the instructions further program the one or more processors to:

receive, by the one or more servers, from a second merchant of the plurality of merchants, a visual representation representative of a second item offered for sale by the second merchant;

associate, by the one or more servers, the visual representation representative of the second item with the second item; and

store, by the one or more servers, the visual representation representative of the second item the visual representation data based on an association with the second item.

10. The system of claim 1 , wherein efficacy data indicates an efficacy of associations between the plurality of visual representations and respective items of the plurality of items.

11. The system of claim 1 , wherein the instructions further program the one or more processors to:

based at least in part on the transaction data, process, by the one more servers, payments for the transactions on behalf of the plurality of merchants.

12. One or more non-transitory computer-readable media storing instructions executable by a one or more processors, wherein the instructions program the one or more processors to:

receive, by one or more servers of a service provider and from point-of-sale (POS) devices of a plurality of merchants, transaction data associated with transactions of the plurality of merchants and associated with a plurality of items, wherein the transaction data includes, for an individual transaction of the transactions, an indication of a corresponding merchant, of the plurality of merchants, conducting the individual transaction and an indication of one or more items purchased in the individual transaction, wherein the indication of the one or more items includes corresponding descriptors and visual representations of the one or more items;

access, by the one or more servers, visual representation data associated with a plurality of visual representations corresponding to items, of the plurality of items, that are in inventories of the plurality of merchants;

receive, by the one or more servers and from a POS device, of the POS devices, of a merchant of the plurality of merchants, an indication of intent to add a new item to an inventory associated with the merchant, the indication including one or more descriptors of the new item;

train, by the one or more servers, a data model to output one or more visual representations of an item based on respective descriptors of the item and using at least the transaction data and image data associated with the plurality of items, wherein training data includes efficacy data of previous associations between individual visual representations and corresponding individual items of the plurality of items;

based at least in part on the indication of intent to add the new item, input, by the one or more servers, the one or more descriptors of the new item into the data model;

receive by the one or more servers and from the data model, a merchant-facing visual representation and a customer-facing visual representation for representing the new item, wherein the customer-facing visual representation is selected based on first efficacy data associated with the customer-facing visual representation being associated with a higher conversion rate than second efficacy data associated with the merchant-facing visual representation;

cause presentation, by the one or more servers and via a display of the at least one of the POS device or another merchant device, an approval user interface including a merchant-facing image based at least in part on the merchant-facing visual representation and a customer-facing image based at least in part on the customer-facing visual representation and a request for approval to use the merchant-facing image and the customer-facing image for representing the new item; and

based at least in part on receiving the approval to use the merchant-facing image and the customer-facing image, cause, by the one or more servers, the merchant-facing image to be presented via a merchant-facing user interface and the customer-facing image to be presented via a customer-facing user interface.

13. The one or more non-transitory computer-readable media of claim 12 , wherein the indication of intent to add the new item to the inventory associated with the merchant comprises input by the merchant, via an inventory user interface, wherein the inventory user interface is associated with building a catalog of inventory, the input comprising at least one of:

a description of the new item;

an inventory code associated with the new item; or

a manufacturer associated with the new item.

14. The one or more non-transitory computer-readable media of claim 12 , wherein at least one of:

the merchant-facing image is of a first quality and the customer-facing image is of a second quality, the second quality being greater than the first quality; or

the merchant-facing visual representation is of a third quality and the customer-facing visual representation is of a fourth quality, the fourth quality being greater than the third quality.

15. The one or more non-transitory computer-readable media of claim 12 , wherein the instructions further program the one or more processors to:

analyze, by the one or more servers, one or more websites displaying visual representations; and

compare, by the one or more servers, the visual representations with a description associated with the new item, the description provided by the merchant in the indication of intent to add the new item,

wherein obtaining the merchant-facing visual representation and the customer-facing visual representation is further based at least in part on comparing visual representations images with the description.

16. The one or more non-transitory computer-readable media of claim 12 , wherein the instructions further program the one or more processors to:

verify, by the one or more servers, that a first license associated with the merchant-facing visual representation and a second license associated with the customer-facing visual representation are appropriate for use by the merchant.

17. The one or more non-transitory computer-readable media of claim 12 , wherein the instructions further program the one or more processors to:

identify, by the one or more servers, at least one of a first license associated with the merchant-facing visual representation or a second license associated with the customer-facing visual representation; and

determine, by the one or more servers, that the at least one of the first license or the second license is issued to a public domain,

wherein the request for approval is based at least in part on the at least one of the first license or the second license being issued to the public domain.

18. A computer-implemented method comprising:

receiving, by one or more servers of a service provider and from point-of-sale (POS) devices of a plurality of merchants, transaction data associated with transactions of the plurality of merchants and associated with a plurality of items, wherein the transaction data includes, for an individual transaction of the transactions, an indication of a corresponding merchant, of the plurality of merchants, conducting the individual transaction and an indication of one or more items purchased in the individual transaction, wherein the indication of the one or more items includes corresponding descriptors and visual representations of the one or more items;

accessing, by the one or more servers, visual representation data associated with a plurality of visual representations corresponding to items, of the plurality of items, that are in inventories of the plurality of merchants;

receiving, by the one or more servers and from a POS device, of the POS devices, of a merchant of the plurality of merchants, an indication of intent to add a new item to an inventory associated with the merchant, the indication including one or more descriptors of the new item;

training, by the one or more servers, a data model to output one or more visual representations of an item based on respective descriptors of the item and using at least the transaction data and image data associated with the plurality of items, wherein training data includes efficacy data of previous associations between individual visual representations and corresponding individual items of the plurality of items;

based at least in part on the indication of intent to add the new item, inputting, by the one or more servers, the one or more descriptors of the new item into the data model;

receiving by the one or more servers and from the data model, a merchant-facing visual representation and a customer-facing visual representation for representing the new item, wherein the customer-facing visual representation is selected based on first efficacy data associated with the customer-facing visual representation being associated with a higher conversion rate than second efficacy data associated with the merchant-facing visual representation;

causing presentation, by the one or more servers and via a display of the at least one of the POS device or another merchant device, an approval user interface including a merchant-facing image based at least in part on the merchant-facing visual representation and a customer-facing image based at least in part on the customer-facing visual representation and a request for approval to use the merchant-facing image and the customer-facing image for representing the new item; and

based at least in part on receiving the approval to use the merchant-facing image and the customer-facing image, causing, by the one or more servers, the merchant-facing image to be presented via a merchant-facing user interface and the customer-facing image to be presented via a customer-facing user interface.

19. The computer-implemented method of claim 18 , further comprising:

analyzing, by the one or more servers, one or more websites displaying visual representations; and

comparing, by the one or more servers, the visual representations with a description associated with the new item, the description provided by the merchant in the indication of intent to add the new item,

wherein obtaining the merchant-facing visual representation and the customer-facing visual representation is further based at least in part on comparing visual representations images with the description.

20. The computer-implemented method of claim 18 , wherein the plurality of merchants can access the visual representation data via respective instances of a point-of-sale (POS) application executable by the POS devices, and wherein an instance of the POS application configures a device to process transactions via the service provider on behalf of the merchant.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 8, 2023
From: CAPERS, MATTHEW; GAVALDA, MARSAL; JHUNJA, ROSHAN
To: SQUARE, INC.
Reel/Frame 063570/0562 →
CHANGE OF NAME Recorded May 8, 2023
From: SQUARE, INC.
To: BLOCK, INC.
Reel/Frame 063573/0880 →
Continuity (1)
Continuation 16204556 · Nov 29, 2018
References Cited (84)
US 5168445A · Kawashima et al. · 1992 [cited by applicant]
US 6035284A · Straub et al. · 2000 [cited by applicant]
US 6298331B1 · Walker et al. · 2001 [cited by applicant]
US 7013290B2 · Ananian · 2006 [cited by applicant]
US 7589628B1 · Brady · 2009 [cited by applicant]
US 7720708B1 · Elkins, II et al. · 2010 [cited by applicant]
US 8355954B1 · Goldberg et al. · 2013 [cited by applicant]
US 8650062B2 · Krech · 2014 [cited by applicant]
US 8725594B1 · Davies et al. · 2014 [cited by applicant]
US 8775401B2 · Zhou et al. · 2014 [cited by applicant]
US 8831998B1 · Cramer et al. · 2014 [cited by applicant]
US 9152724B1 · Eitreim et al. · 2015 [cited by applicant]
US 9280560B1 · Dube et al. · 2016 [cited by applicant]
US 9323441B1 · Minks-Brown et al. · 2016 [cited by applicant]
US 9505554B1 · Kong et al. · 2016 [cited by applicant]
US 9659310B1 · Allen et al. · 2017 [cited by applicant]
US 9779447B2 · Paolini · 2017 [cited by applicant]
US 10140623B1 · Lloyd et al. · 2018 [cited by applicant]
US 10373118B1 · Lefkow et al. · 2019 [cited by applicant]
US 10776626B1 · Lin et al. · 2020 [cited by applicant]
US 10783509B2 · Pattarawuttiwong · 2020 [cited by applicant]
US 10878394B1 · Gjertson et al. · 2020 [cited by applicant]
US 11080674B1 · Chen et al. · 2021 [cited by applicant]
US 11481749B1 · Gjertson et al. · 2022 [cited by applicant]
US 11645613B1 · Capers et al. · 2023 [cited by applicant]
US 20020174000A1 · Katz et al. · 2002 [cited by applicant]
US 20030216969A1 · Bauer et al. · 2003 [cited by applicant]
US 20040186783A1 · Knight et al. · 2004 [cited by applicant]
US 20040215539A1 · Doi et al. · 2004 [cited by applicant]
US 20050246245A1 · Satchell et al. · 2005 [cited by applicant]
US 20050283404A1 · Young · 2005 [cited by applicant]
US 20060149639A1 · Liu et al. · 2006 [cited by applicant]
US 20090259569A1 · Narea et al. · 2009 [cited by applicant]
US 20090281884A1 · Selinger et al. · 2009 [cited by applicant]
US 20110054992A1 · Liberty et al. · 2011 [cited by applicant]
US 20110082735A1 · Kannan et al. · 2011 [cited by applicant]
US 20110161207A1 · Moussavi et al. · 2011 [cited by applicant]
US 20110246215A1 · Postma et al. · 2011 [cited by applicant]
US 20110258083A1 · Ren · 2011 [cited by applicant]
US 20110320246A1 · Tietzen et al. · 2011 [cited by applicant]
US 20120271740A1 · Connors et al. · 2012 [cited by applicant]
US 20120278154A1 · Lange et al. · 2012 [cited by applicant]
US 20120278205A1 · Chin · 2012 [cited by applicant]
US 20130185152A1 · Aaron et al. · 2013 [cited by applicant]
US 20130325554A1 · Ouimet · 2013 [cited by applicant]
US 20130325672A1 · Odenheimer et al. · 2013 [cited by applicant]
US 20140244416A1 · Venkat et al. · 2014 [cited by applicant]
US 20140279204A1 · Roketenetz et al. · 2014 [cited by applicant]
US 20140289167A1 · Rosenberg et al. · 2014 [cited by applicant]
US 20150073925A1 · Renfroe · 2015 [cited by applicant]
US 20150166210A1 · Schram et al. · 2015 [cited by applicant]
US 20150178654A1 · Glasgow et al. · 2015 [cited by applicant]
US 20150278912A1 · Melcher et al. · 2015 [cited by applicant]
US 20150310383A1 · Iser et al. · 2015 [cited by applicant]
US 20160104175A1 · Fanourgiakis et al. · 2016 [cited by applicant]
US 20160275424A1 · Concannon et al. · 2016 [cited by applicant]
US 20160314528A1 · Abbott et al. · 2016 [cited by applicant]
US 20170032310A1 · Mimnaugh · 2017 [cited by applicant]
US 20170286980A1 · Winters et al. · 2017 [cited by applicant]
US 20180039965A1 · Han et al. · 2018 [cited by applicant]
US 20180047192A1 · Kristal et al. · 2018 [cited by applicant]
US 20180101875A1 · Kim et al. · 2018 [cited by applicant]
US 20180204256A1 · Bifolco et al. · 2018 [cited by applicant]
US 20180315111A1 · Alvo et al. · 2018 [cited by applicant]
US 20180365753A1 · Fredrich et al. · 2018 [cited by applicant]
US 20190080277A1 · Trivelpiece et al. · 2019 [cited by applicant]
US 20190109916A1 · Varghese et al. · 2019 [cited by applicant]
US 20190132715A1 · Marzouk · 2019 [cited by applicant]
US 20190236528A1 · Brooks et al. · 2019 [cited by applicant]
US 20190236531A1 · Adato et al. · 2019 [cited by applicant]
US 20190266554A1 · Lin et al. · 2019 [cited by applicant]
US 20190266654A1 · Gadre et al. · 2019 [cited by applicant]
US 20190272497A1 · Tingler et al. · 2019 [cited by applicant]
US 20190295148A1 · Lefkow et al. · 2019 [cited by applicant]
US 20190306137A1 · Isaacson et al. · 2019 [cited by applicant]
US 20190310126A1 · Gurumohan et al. · 2019 [cited by applicant]
US 20190325498A1 · Clark · 2019 [cited by applicant]
WO 2013026167A1 · 2013 [cited by applicant]
Deng, S., “Stock Price Change Rate Prediction by Utilizing Social Network Activities”, The Scientific World Journal, vol. 14, Article ID 861641, 14 pages (Mar. 25, 2014). [cited by applicant]
“Internal Revenue Bulletin: 2004-31” Internal Revenue Bulletin, Aug. 2, 2004, 146 pages. [cited by applicant]
Steven, Top 14 reasons why customers return purchases, 3C Contact Services, Aug. 18, 2016, 3 pages. [cited by applicant]
“Creating Items with Square Point of Sale—YouTube” Square, Retrived from the Internet URL: https://www.youtube.com/watch?v=il2CPaPrUK4, Jun. 16, 2015, pp. 1-3. [cited by applicant]
“Image | Definition of Image”, Merriam Webster, Retrived from the Internet URL: https://www.merriam-webster.com/dictionary/image, on Oct. 28, 2020, pp. 1-16. [cited by applicant]
Prakash P., “Square Inventory Items—Step by Step Guide”, Retail>Bricks and Mortar, Ultimate Guide, Jul. 16, 2017, pp. 1-12. [cited by applicant]