WO2019199530A1 - Systèmes et procédés concernant une optimisation de point de reconnaissance d'achats d'utilisateur sur site au niveau d'un emplacement physique - Google Patents

Systèmes et procédés concernant une optimisation de point de reconnaissance d'achats d'utilisateur sur site au niveau d'un emplacement physique Download PDF

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Publication number
WO2019199530A1
WO2019199530A1 PCT/US2019/025484 US2019025484W WO2019199530A1 WO 2019199530 A1 WO2019199530 A1 WO 2019199530A1 US 2019025484 W US2019025484 W US 2019025484W WO 2019199530 A1 WO2019199530 A1 WO 2019199530A1
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WIPO (PCT)
Prior art keywords
purchasable
user
unit
optimizer
point
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PCT/US2019/025484
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English (en)
Inventor
Bartley J. MADDEN
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Bartley J Madden Foundation
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Bartley J Madden Foundation
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Publication date
Priority claimed from US15/953,187 external-priority patent/US10062069B1/en
Application filed by Bartley J Madden Foundation filed Critical Bartley J Madden Foundation
Publication of WO2019199530A1 publication Critical patent/WO2019199530A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/08—Payment architectures
    • G06Q20/20—Point-of-sale [POS] network systems
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/08—Payment architectures
    • G06Q20/20—Point-of-sale [POS] network systems
    • G06Q20/202—Interconnection or interaction of plural electronic cash registers [ECR] or to host computer, e.g. network details, transfer of information from host to ECR or from ECR to ECR
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/30—Payment architectures, schemes or protocols characterised by the use of specific devices or networks
    • G06Q20/32—Payment architectures, schemes or protocols characterised by the use of specific devices or networks using wireless devices
    • G06Q20/322—Aspects of commerce using mobile devices [M-devices]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/30—Payment architectures, schemes or protocols characterised by the use of specific devices or networks
    • G06Q20/32—Payment architectures, schemes or protocols characterised by the use of specific devices or networks using wireless devices
    • G06Q20/322—Aspects of commerce using mobile devices [M-devices]
    • G06Q20/3224—Transactions dependent on location of M-devices
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07G—REGISTERING THE RECEIPT OF CASH, VALUABLES, OR TOKENS
    • G07G1/00—Cash registers
    • G07G1/0036—Checkout procedures
    • G07G1/0045—Checkout procedures with a code reader for reading of an identifying code of the article to be registered, e.g. barcode reader or radio-frequency identity [RFID] reader
    • G07G1/0081—Checkout procedures with a code reader for reading of an identifying code of the article to be registered, e.g. barcode reader or radio-frequency identity [RFID] reader the reader being a portable scanner or data reader

Definitions

  • each of the competing purchasable-unit distributions which includes the outbidding purchasable-unit distributor, can access a user-centric information profile in order to generate competing bids.
  • the user-centric information profile may include details about the user’s past purchase history or other personal information to allow the distributors to generate informed and data-driven offers or advertisements targeted to the user.
  • the outbidding purchasable-unit distributor is the distributor that wins the bidding process and therefore is able to generate the offer received by the optimizer device, and, therefore the user.
  • the plurality of competing purchasable-unit distributors can include one or more product manufacturers and one or more product wholesalers who distributed the corresponding competing purchasable-units to a physical store for onsite identification and selection by consumers.
  • the chosen purchasable-unit may be detected with one or more sensors associated with a user container when the user places the chosen purchasable-unit in the user container.
  • the user container can be, for example, a shopping cart, shopping basket, or other designated location or container at the physical location that the user places the chosen purchasable-unit.
  • the optimizer device can initiate a purchase request, based on the chosen purchasable-unit identifier (ID), to purchase the chosen purchasable-unit when the user is within a proximity to an exit of the physical location.
  • the optimizer device can cause an update to a user-centric information profile associated with the user.
  • the point-of-recognition optimizer systems and methods allow for distributors to access a user’s user-centric information profile to analyze information about the consumer and bid on the opportunity to transmit offers, which can include advertisements and coupons, at the exact time when consumers are about to make a purchase decision.
  • Figure 3 illustrates an embodiment of a consumer purchase procedure in accordance with the point-of-recognition optimizer systems and methods described herein.
  • Figure 4 illustrates an embodiment of a checkout process in accordance with the point- of-recognition optimizer systems and methods described herein.
  • the local point-of-recognition optimizer servers 104 may also implement one or more database platforms for storing and organizing the user-center information profiles and other user information, which may include, for example, Oracle Database, IBM DB2, MySQL, MongoDB, or other such database platforms.
  • network 130 may be a public network, such as the Internet, where store 102, and its local point-of-recognition servers 104, and remote point-of-recognition optimizer servers 140 communicate over conventional Internet protocols and standards, for example, including the Hyper Text Transfer Protocol (HTTP), Transfer Control Protocol (TCP), and the Internet Protocol (IP).
  • HTTP Hyper Text Transfer Protocol
  • TCP Transfer Control Protocol
  • IP Internet Protocol
  • the remote point-of-recognition optimizer servers 140 may be similarly configured to the local point-of- recognition optimizer servers 104 such that the remote point-of- recognition optimizer servers 140 also include one or more processors configured to optimize onsite user purchases at a physical location as described herein.
  • the remote point-of- recognition optimizer servers 140 may also include one or more memories for storing
  • the local point-of-recognition optimizer servers 104 may implement the functionality regarding receiving a purchasable-unit identifier (ID) associated with a recognized purchasable-unit identified by an optimizer device, determining a plurality of competing purchasable-units based on the purchasable-unit ID, and transmitting an offer for an offered purchasable-unit to the optimizer device, where the remote point-of-recognition optimizer servers 140 may implement the functionality of receiving a purchase request and updating a user centric information profile associated with the user based on the purchase request.
  • ID purchasable-unit identifier
  • the optimizer device 110 may be provided by the owner or operator of store 102 to user 106 when user 106 enters store 102.
  • user 106 may receive the optimizer device from store personnel (or from a designated pickup location) of store 102 when user 106 enters the store, where the user 106 may return the optimizer device 110 to the store personnel (or designed pickup location) when user 106 exits the store.
  • the optimizer device 110 may be configured to interact with any of the local point-of-recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140 to optimize onsite user purchases at store 102 as described herein.
  • the optimizer device 110 may also include a transceiver for transmitting and receiving computer transmissions to and from network 130 and, therefore, through network 130 to any of the local point-of-recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140.
  • network 130 may include a wireless transceiver 126 for facilitating transmissions 124 to and from user 106’ s optimizer device 110.
  • the transceiver 126 may be located onsite at store 102 such that when user 106 enters store 102, the point-of-recognition optimizer system can begin to interact with the user 106’ s optimizer device 110 through private store network 123 and transceiver 126, for example, by requesting login information from the user 106 in order to activate the optimizer device 110 with the point-of-recognition optimizer system.
  • the transceiver 126 may be a cellular network tower, base station, or other mobile phone base station that can send and receive transmissions 124 to and from optimizer device 110.
  • the transmissions 124 may be based on any of a number of mobile communication standards including GSM, EDGE, UMTS/ETTRA, 3GPP, LTE, CDMA, UMB, or other such mobile phone standards.
  • the transmissions 124 may be sent to and from the optimizer device 110 via a mobile base station transceiver 126, where the transmissions may be routed through network 130 to any of the local point-of-recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140.
  • the optimizer device 110 may include a global positing satellite (GPS) unit, such as a GPS microchip within the optimizer device 110, which may be used to determine the position of user 106.
  • GPS global positing satellite
  • the GPS unit can detect when user 106 enters store 102, so that the point-of-recognition optimizer system can begin to interact with the user 106’ s optimizer device 110, for example, by requesting login information from the user 106 in order to active the optimizer device 110 with the point-of-recognition optimizer system.
  • User 106 may also interact with a user container 108, which, in some embodiments, can be an optimizer shopping cart or shopping basket as described herein.
  • the user container 108 may include one or more sensors, such as infrared (IR) sensors, motion detection sensors, image detection sensors, weight detection sensors, accelerometers, gyro sensors, or other such sensors, for detecting when a user places or removes a purchasable-unit in or from the user container.
  • the user container 108 may be located onsite at store 102 and may be provided by the store 102 owner or operator user 106 when user 106 enters store 102.
  • the user container 108 may also include a transceiver for sending wireless transmissions, such as Bluetooth standard wireless transmissions, to and from the optimizer device 110.
  • the user container 108 may include a wired interface, such as a universal serial bus (USB), to provide a wired connection (not shown) for connecting the user container 108 to the optimizer device 110 to facilitate optimizing onsite user purchases at a physical location as described herein.
  • USB universal serial bus
  • user 106 may provide user information to the store 102 owner or operator. For example, in one embodiment user 106 may enter user information via optimizer device 110 for upload to any of the local point-of-recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140.
  • the user information may include information about the user, for example, the user’s name, home address, email address, credit score, net worth, or other such information.
  • the user information may also include document based information, including information from the user 106’ s tax bills, real estate records, utility bills, automobile records, insurance cards, vehicle registrations, and the like.
  • the information may be entered via the optimizer device 110, such as via the user inputting the information via a keyboard of the optimizer device 110.
  • the user information may be entered via an optical unit, such as camera or image sensor associated with the optimizer device, where the user 106 takes a picture or otherwise scans the document such that the user information is sourced and captured directly from the document.
  • the optical sourced user-centric information may include information from document(s) such as real estate tax bills, car insurance documents, and the like. This visual process may verify the validity of the data inputted, where a copy of the document, together with its information, may be stored within the computer memory of the local point-of- recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140, and can be used for authentication and/or validity purposes.
  • authentication and/or validity can include comparing the optical sourced user-centric information/document to trusted user information, such as user credit card information or equivalent information, such that the user-centric information is verified against trusted information of the user.
  • Optical sourcing can include the use of object character recognition (OCR), where the characters and text of the document are identified from the optical source and used to digitally create an electronic version of the information for upload to and storage with any of the local point-of-recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140.
  • OCR object character recognition
  • a display screen of the optimizer device 110 may display a user-centric information profile as described herein and may be used to input personal data such as real estate tax bills, car insurance documents, and the like.
  • the optical recognition capability of the optimizer device 110 may capture the consumer’s name and address and may cross-check with consumer’s credit card or equivalent data. In this manner, such user-centric information/personal data is verified.
  • user 106 may input the information via another device, such as user laptop 120.
  • the user may enter or upload information or documents to any of local point-of-recognition optimizer servers 104 or remote point-of- recognition optimizer servers 140 from user laptop 120 via network 130.
  • the user laptop 120 may be connected to network 130, and, therefore local point-of-recognition optimizer servers 104 and remote point-of-recognition optimizer servers 140, via connection 122, which can be, for example an Internet connection.
  • the user information may be used to generate or update a user centric information profile.
  • the user information and a user-centric information profile may be stored on and accessed from the computer memory and/or databases of local point-of-recognition optimizer servers 104 or remote point-of-recognition optimizer servers 140.
  • the user-centric information profile may contain all of the data and information uploaded by user 106.
  • the user centric information profile may contain a user identifier (ID) that uniquely identifies user 106 in the point-of-recognition optimizer system.
  • the user-centric information profile may also contain a user score or ranking, which ranks the user 106 as compared with other users of the system.
  • user 106 may use the optimizer device 110 to identify and recognize a purchasable-unit and its related purchasable-unit ID.
  • the point-of-recognition optimizer servers 104 or 140 may then determine a plurality of competing purchase-units based on the recognized purchasable unit’s purchasable-unit ID, where each of the competing purchase-units correspond to purchasable-units manufactured by, distributed by, or otherwise provided by each competing purchasable-unit distributors A-C 150.
  • Each the competing purchasable-unit distributor servers A-C may then each receive, from the point-of-recognition optimizer servers 104 and/or 140, the user ID of user 106 and an indication of a competing purchasable-unit that is manufactured, distributed, or otherwise provided by the competing purchasable-unit distributor.
  • Each of the competing purchasable-unit distributor servers A-C (152-156) may access user l06’s user-centric information profile, using the user 106’ s user ID, to receive user 106’ s user information, user score, or other information that is stored for user 106 at the local point-of-recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140.
  • the competing purchasable- unit distributor servers A-C (152-156) may each receive the user l06’s user-centric information profile, which includes the user ID of user 106 and other information, such that the competing purchasable-unit distributor servers A-C (152-156) would not need to access the local point-of- recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140 to retrieve the user 106’ s user-centric information profile or related information.
  • each of the competing purchasable-unit distributors A-C 150 may bid on the opportunity to send an offer to the user l06’s optimizer device 110.
  • the offer may be for the distributor’s indicated competing purchasable-unit that is available from the distributor, and may include a discount, coupon, advertisement, incentive, or other message related to the respective distributor’s competing purchasable-unit.
  • a given bid may be an electronic transmission to the store 102 owner or operators, such as to the local point of-recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140, and may include a fee-based bid that includes an indication of a fee that a respective competing purchasable-unit distributor A-C 150 (e.g., competing purchasable-unit distributor A) is willing to pay to the store 102 owner or operator for the opportunity of user l06’s optimizer device 110 to receive an offer (e.g., from the competing purchasable-unit distributor A).
  • a respective competing purchasable-unit distributor A-C 150 e.g., competing purchasable-unit distributor A
  • the competing purchasable-unit distributors A-C 150 (e.g., competing purchasable-unit distributor A) that outbids the other competing purchasable-unit distributors A-C 150 (e.g., competing purchasable-unit distributors B and C) is the outbidding distributor and may send the offer to the point-of-recognition servers 104 and/or 140, where the offer may be routed and transmitted by the point-of-recognition servers 104 and/or 140 to the optimizer device 110 for display to user 106.
  • competing purchasable-unit distributors A-C 150 e.g., competing purchasable-unit distributor A
  • competing purchasable-unit distributors A-C 150 is the outbidding distributor and may send the offer to the point-of-recognition servers 104 and/or 140, where the offer may be routed and transmitted by the point-of-recognition servers 104 and/or 140 to the optimizer device 110 for display to user 106.
  • the user 106 may then chose to accept the offer, for example, by inputting an acceptance selection via the optimizer device 110 or by placing the offered purchasable-unit in the user container 108 as further described herein.
  • the user 106 may also chose to reject the offer by choosing a different purchasable-unit or by not purchasing any purchasable-unit.
  • Figure 2 illustrates an embodiment of a consumer-oriented purchase transaction using the point-of-recognition optimizer systems and methods described herein.
  • consumer 206 corresponds to user 106
  • optimizer shopping cart 208 corresponds to user container 108 of Figure 1, respectively, where each of consumer 206 and optimizer shopping cart 208 are specific embodiments of user 106 and user container 108, respectively.
  • the disclosure of Figure 1 for user 106 and user container 108 apply similarly herewith with respect to Figure 2.
  • consumer 206 may enter a physical store, such as store 102, and receive the optimizer shopping cart 208.
  • the optimizer shopping cart 208 includes an optimizer device 210.
  • Optimizer device 210 corresponds to the optimizer device 110 of Figure 1, and, accordingly, the disclosure of Figure 1 for the optimizer device 110 applies similarly herewith with respect to Figure 2.
  • the optimizer device 210 is an electronic device including one or more processors, software, including, for example, mobile App software (e.g., mobile App software based on Apple iOS, Google Android, or other mobile App platform software), and a display screen that may be viewed by consumer 206.
  • mobile App software e.g., mobile App software based on Apple iOS, Google Android, or other mobile App platform software
  • the sensors of the sensor field 220 communicate, via wired or wireless transmission, with the optimizer device 210, where the user’s placement of a purchasable-unit in the optimizer shopping cart 208 can cause the optimizer to display a price or other information on the display screen of the optimizer device 210.
  • the point-of-recognition optimizer servers 104 and/or 140 may also be configured to communicate with a user container (e.g., shopping cart 208), either directly or indirectly via an optimizer device (e.g., optimizer device 210).
  • a user container e.g., shopping cart 208
  • an optimizer device e.g., optimizer device 210
  • the point-of-recognition optimizer servers 104 and/or 140 may store instructions, e.g., in computer memory of the point-of-recognition optimizer servers 104 and/or 140, for identification of purchasable-units via related purchasable-unit IDs.
  • One or more processors, as described herein, of the point-of-recognition optimizer servers 104 and/or 140 may be configured to execute the instructions.
  • the point-of-recognition optimizer servers 104 and/or 140 may be communicatively coupled to a wireless transceiver (e.g., wireless transceiver 126).
  • the wireless transceiver may send and receive wireless transmissions using any one or more of the Bluetooth, WiFi, or cellular wireless transmission standards.
  • the wireless transceiver (e.g., wireless transceiver 126) may be communicatively coupled either directly to the point-of-recognition optimizer servers 104 and/or 140 or indirectly, e.g., via a network (e.g., network 130, private store network 123, etc.).
  • a user container may have one or more sensors (e.g., the sensors of the sensor field 220) and a wireless transceiver (not shown).
  • the wireless transceiver of the user container may be configured to send and receive wireless computer transmissions to and from at least one of (1) a wireless transceiver of an optimizer device (e.g., optimizer device 210) as associated with a user, or (2) the wireless transceiver (e.g., wireless transceiver 126) of point-of-recognition optimizer servers 104 and/or 140.
  • the user container is onsite at the physical location and may be configured to detect, via the one or more sensors (e.g., the sensors of the sensor field 220), a chosen purchasable-unit when the user places the chosen purchasable-unit in the user container (e.g., shopping cart 208).
  • the chosen purchasable-unit may have a plurality of surfaces (e.g., the plurality of surfaces of product packaging, a box, etc.).
  • the chosen purchasable-unit ID may be identifiable, via one or more sensors (e.g., the sensors of the sensor field 220), on one or more of the plurality of surfaces.
  • the one or more sensors may identify the placement of the chosen purchasable-unit in the shopping cart 208 when the chosen purchasable-unit contains an invisible Digimarc barcode (e.g., as described herein) imprinted one or more surfaces of the purchasable-unit product packaging.
  • the purchasable-unit ID may be based on the Digimarc standard or otherwise use the Digimarc based standard, for example, where the purchasable-unit ID is encoded on the one or more surfaces of purchasable-unit product packaging using the Digimarc based standard.
  • the chosen purchasable-unit may be associated with a radio frequency identification (RFID) tag.
  • RFID radio frequency identification
  • the chosen purchasable-unit ID is identifiable, via one or more sensors (e.g., the sensors of the sensor field 220), from the RFID tag, where the RFID tag has encoded the chosen purchasable-unit ID.
  • the one or more sensors may be arrayed to recognize the RFID tag when a user places the chosen purchasable-unit in the shopping cart 208.
  • a user container may include one or more sensor indicators (not shown).
  • the one or more sensor indicators may be configured to indicate a status of the one or more sensors (e.g., a status of the sensors of the sensor field 220).
  • the one or more sensor indicators may be configured to visually or audibly indicate the status of the one or more sensors (e.g., the sensors of the sensor field 220).
  • the one or more sensor indicators may visually emit different color indications, or different audible tones, indicating that the one or more sensors of the user container successfully detected (or failed to detect) a chosen purchasable-unit ID of a chosen a purchasable-unit.
  • the status of the one or more sensors may indicate at least one of a success status or a failure status, where the one or more sensor indicators are configured to indicate the success status or failure status when the user places the chosen purchasable-unit in the user container.
  • the normal color of the sensor indicator(s) e.g., indicators of the sensors of the sensor field 220
  • the sensor indicator(s) may flash or change to green.
  • the sensor indicators(s) may flash or change to red.
  • a user may readjust the position of the chosen purchasable-unit in the user container (e.g., shopping cart 208) to attempt a successful identification by the sensors (e.g., the sensors of the sensor field 220), which may be indicated by the sensor indicator(s) turning green.
  • the point-of-recognition optimizer servers 104 and/or 140 may receive a wireless transmission indicating the error. In such situations, the consumer may subsequently need to utilize a manual checkout procedure (e.g., checkout lane or station in the store 102).
  • the one or more processors of the point-of-recognition optimizer servers 104 and/or 140 may be configured to receive, via the communicatively coupled wireless transceiver (e.g., wireless transceiver 126), a purchasable-unit ID associated with the chosen purchasable-unit from at least one of (1) the wireless transceiver of the optimizer device (e.g., optimizer device 210), or (2) the wireless transceiver of the user container.
  • the communicatively coupled wireless transceiver e.g., wireless transceiver 126
  • a purchasable-unit ID associated with the chosen purchasable-unit from at least one of (1) the wireless transceiver of the optimizer device (e.g., optimizer device 210), or (2) the wireless transceiver of the user container.
  • the point-of-recognition optimizer servers 104 and/or 140 are able to receive, either directly from the user container (e.g., shopping cart 208), or indirectly from the optimizer device (e.g., optimizer device 210), a purchasable-unit ID associated with a chosen purchasable-unit that the user placed in the user container (e.g., shopping cart 208).
  • the one or more processors of the point-of-recognition optimizer servers 104 and/or 140 may be configured to determine a plurality of competing purchasable-units based on the purchasable-unit ID.
  • the determination may include the optimizer server sending the purchasable-unit ID to one or more distributor servers associated with a plurality of competing purchasable-unit distributors.
  • the determination may further include the optimizer server receiving one or more offers from the one or more distributor servers corresponding to the plurality of competing purchasable-units, where the plurality of competing purchasable-units are located either onsite at the physical location or offsite of the physical location.
  • the one or more processors of the point-of-recognition optimizer servers 104 and/or 140 may transmit, via a second computer transmission to the optimizer device (e.g., optimizer device 210), an offer for an offered purchasable-unit.
  • the offer may originate from the one or more distributor servers of an outbidding purchasable-unit distributor, where the offer was chosen from the one or more offers such that the one or more distributor servers of the outbidding purchasable-unit distributor outbid the one or more distributor servers of all other distributors from the plurality of competing purchasable-unit distributors for an opportunity of the optimizer device to receive the offer.
  • the point-of-recognition optimizer servers 104 and/or 140 may be configured to determine that an interference threshold value has been passed regarding the user’s interaction with the user container (e.g., shopping cart 208). In such embodiments, the point-of-recognition optimizer servers 104 and/or 140 may be further configured to generate, based on the interference threshold value, an alert, the alert indicating to onsite personnel at the physical location to assist the user.
  • the point-of-recognition optimizer servers 104 and/or 140 may be configured to initiate a purchase request, based on the purchasable-unit ID, to purchase the chosen purchasable-unit on behalf of the user when the user is within a proximity to an exit of the physical location.
  • the point-of-recognition optimizer servers 104 and/or 140 may update a user-centric information profile associated with the user based on the purchase request.
  • Product A 205 may be one of several competing purchasable-units available onsite at store 102, where product A 205 may be stocked in a similar physical onsite location, such as storage shelf 207 within store 102, with other competing purchasable-unit products distributed by other competing purchasable-unit distributors, including competing manufactures or wholesalers, for example, competing purchasable-unit distributors A-C 250.
  • competing purchasable-unit distributors A-C 250 are depicted as competing manufacturers, but that correspond to the competing purchasable-unit distributors A-C 150 of Figure 1. Accordingly, the disclosure of Figure 1 for the competing purchasable-unit distributors A-C applies similarly herewith with respect to Figure 2.
  • the optimizer device 210/ hand-held product identifier 202 can identify a purchasable-unit ID simply being pointed at, or by being within a vicinity of, the related purchasable-unit. Such embodiments avoid the conventional procedure of having to specifically locate a UPC barcode on a given product.
  • Digimarc barcode that is invisible and embedded over the entire packaging of a product.
  • Use of the Digimarc barcode would allow a purchasable- unit ID to be provided on a plurality of surfaces of a purchasable-unit, and would avoid the need for identification of a UPC barcode.
  • the purchasable-unit identifier (ID) associated with the purchasable-unit product A 205 may be received by the point-of- recognition optimizer system (not shown) including, for example, any of the local point-of- recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140 of Figure 1.
  • the point-of-recognition optimizer servers 104 and/or 140 may then determine a plurality of competing purchase-units based on the recognized purchasable unit’s purchasable- unit ID.
  • the plurality of competing purchase-units may include the recognized purchasable-unit (e.g., purchasable-unit product A 205) as identified by the optimizer device 2l0/hand-held product identifier 202, and also one or more additional purchasable-units.
  • the one or more additional purchasable-units may include the remaining, competing purchasable-units located on storage shelf 207.
  • the one or more additional purchasable-units may include offsite, competing purchase-units that are available from offsite distributors, including manufacturers and/or wholesalers, who do not yet have their purchasable-units in inventory or display at the store 102.
  • purchasable-unit distributor C as shown in Figures 1 and 2 may be an offsite distributor.
  • the offsite distributors e.g., such as distributor C
  • the offsite distributor C may, however, benefit by not having to purchase floor or shelf space at store 102 to place purchase-units.
  • the offsite functionally of the optimizer system allows such smaller distributors to offer competitive prices vis-a-vis larger distributors (e.g., distributor A) who may have purchasable-units onsite.
  • a benefit to offsite distributors may be securing a sizable number of consumer sales without having any product at the store 102.
  • the sizable number of consumer sales may lead the owner of store 102 to decide to display the offsite distributor’s product in the store 102.
  • the store 102 owner may already have benefitted through fees earned due to higher bids from the offsite distributor.
  • consumers may benefit from offers from the offsite distributor via lower prices and greater variety resulting from increased competition from offsite distributors orchestrated by the features and functionality of optimizer systems and methods as described herein.
  • each of the plurality of competing purchase-units may correspond to purchasable-units manufactured by, distributed by, or otherwise provided by each of the competing purchasable-unit distributors A-C 250, which, as described can be either an onsite distributor, an offsite distributor, or a distributor that offers products in both an onsite and offsite capacity.
  • manufacturer A of competing purchasable-unit distributors A-C 250 would receive an indication that the purchasable-unit product A 205 was a competing purchasable-unit that was determined to be a competing purchasable-unit by virtue of the consumer 206 identifying purchasable-unit product A 205 with the optimizer device 2l0/hand-held product identifier 202.
  • manufacturer B of competing purchasable-unit distributors A-C 250 would receive an indication that purchasable-unit product B (not shown, but included on storage shelf 207) was a competing purchasable-unit that was determined to be a competing purchasable-unit by virtue of being a similar or competing product to purchasable-unit product A 205.
  • Manufacturer C would receive similar information.
  • each of the competing purchasable-unit distributors A-C 250 may access a store database 212 that maintains a history of consumer 206’ s purchases and related personal information.
  • the store database 212 can include consumer 206’ s user-centric information profile and other user information and may be stored in any of any of the local point- of-recognition optimizer servers 104 or the remote point-of-recognition optimizer servers 140, as described herein for Figure 1.
  • each of the competing purchasable-unit distributors A-C 250 may bid on the opportunity of the optimizer device 210 to receive an offer from the outbidding distributor.
  • manufacture A may outbid manufacturers B and C by agreeing to pay an advertising fee to the owner or operators of the physical store, such as store 102, where consumer 206 is onsite at.
  • the offer 214 may incentivize consumer 206 to purchase the purchasable-unit of product A 205.
  • the user can place the purchasable-unit product A 205 in the optimizer shopping cart 208 indicating a desire to purchase purchasable-unit product A 205.
  • the sensor field 220 can detect that the purchasable-unit product A 205 has been placed in the optimizer shopping cart 208 and that consumer 206 has not crossed an interference threshold value by overly tampering with the placement or arrangement of the purchasable-unit product A 205 within the optimizer shopping cart 208.
  • the point-of-recognition system can begin a consumer purchase procedure 230, which is more fully described in Figure 3, where the consumer purchase procedure 230 includes sending a purchase request, based on the chosen purchasable-unit ID, so that the consumer 206 may purchase the related chosen purchasable-unit.
  • the purchase request may cause the consumer 206’ s purchase history and/or other user information to be updated with the new purchase transaction, where the new information is stored, for example, in store database 212 on the point-of-recognition optimizer servers 104 and/or 140.
  • FIG. 3 illustrates an embodiment of a consumer purchase procedure 230 in accordance with the point-of-recognition optimizer systems and methods described herein.
  • a product identifier such as an optimizer device 110 or 202/210, may receive a barcode signal (e.g., a signal indicative of the purchasable-unit ID) and may register or identify a specific product, for example, the recognized purchasable-unit identified with the barcode signal.
  • the barcode signal can be received by the optimizer device 110 or 202/210 where the optimizer device 110 or optimizer device 202/210 identifies the purchasable-unit ID via infrared (IR), radio frequency, or image scanning technology.
  • IR infrared
  • product information may be transmitted to the point-of-recognition optimizer system.
  • the product information may include information about the recognized purchasable-unit, including the purchasable-unit ID of the recognized purchasable-unit.
  • Such information can be transmitted to the point-of-recognition optimizer servers 104 and/or 140, where a determination of a plurality of competing purchasable- units can be made based on the purchasable-unit ID.
  • the flow of user and specific product information may be sent to the competing purchasable-unit distributors (e.g., manufacturers) regarding specific products.
  • this can be the competing purchasable-unit distributors A-C of Figures 1 and 2.
  • each of the competing purchasable-unit distributors A-C can receive the user and specific product information, including the user’s user ID, user-centric information profile, and competing product information available of the respective distributor, where such
  • each of the distributors A-C can be used by each of the distributors A-C to generate respective bids for the opportunity of the user’s optimizer device to receive an offer associated with an offered purchasable-unit from the winning, outbidding distributor.
  • the outbidding distributor may transmit the offer to the point-of-recognition optimizer servers 104 and/or 140 for transmission to the consumer’s optimizer device for display.
  • the consumer such as consumer 206 of Figure 2 makes his or her purchase decision by either selecting to purchase the offered purchasable-unit (e.g., product A 205 of Figure 2) or one of the other competing purchasable-units, such the additional competing units of storage shelf 207 of Figure 2 or competing offsite purchasable-units.
  • the consumer 206 may also determine not to buy (310) any of the purchasable-units.
  • the point-of-recognition system may determine whether the chosen purchasable-units are available (314) onsite at the physical location, for example, at store 102.
  • a chosen purchasable-unit is not available (316), then, at block 318, the consumer can elect to have the chosen purchasable-unit delivered to a location specified in a personal information store database, such as store database 212.
  • the chosen purchasable- unit may not be available onsite (e.g., only available via an offsite distributor) or the chosen purchasable-unit may not be in stock (e.g., where an onsite distributor is out of stock of the chosen purchasable-unit) at the physical location, and the consumer may purchase the chosen purchasable-unit, via the optimizer device, for delivery of the chosen purchasable-unit to the user’s home address.
  • the specified address may have been previously stored in the store database 212 so that the consumer need not enter the information again.
  • the consumer may choose to pick up the chosen purchasable-unit at the store, e.g., after receiving a notification email or text that the chosen purchasable-unit is available for pick up.
  • the store-pickup alternative option may reduce the price of the chosen purchasable-unit
  • purchasable-unit because the distributor’s delivery cost may decline as multiple products may be batch delivered to a single location, e.g., store 102.
  • the user may choose the delivery option at time of purchase, where the optimizer device may change the price depending on the delivery option chosen (e.g., a reduced price when the user selects the store-pickup option).
  • the chosen purchasable-units may be detected by the user’s optimizer shopping cart, such as optimizer shopping cart 208, after passing through the cart’s sensor field 220.
  • the chosen purchasable-units may be detected with one or more sensors associated with a user container (e.g., the optimizer shopping cart 208) when the consumer places the chosen purchasable-unit in the user container.
  • the user container can be, for example, a shopping cart, shopping basket, or other device or apparatus for detecting purchasable-units chosen by the user.
  • the number and identity of the chosen purchasable-units may be recorded in the optimizer device’s software, such that the optimizer device (e.g., 202/210) may then determine the total number and type of chosen purchasable-units and compute and display a total price and other purchase-related information including, for example, sales tax information, discount information received from any related offer, or other such purchase-related information on the display screen of the optimizer device 202/210.
  • the optimizer device e.g., 202/210
  • FIG. 4 illustrates an embodiment of a checkout process 400 in accordance with the point-of-recognition optimizer systems and methods described herein.
  • a user such as user 106 or consumer 206, has completed his or her shopping experience at store 102. This can include, for example, after the user has placed his or her chosen purchasable-units in the user container, such as optimizer shopping cart 208.
  • the optimizer machine learning model may provide a unique, context- specific, and/or time- sensitive aggregation of user-centric profile information or other related information that is unavailable to search engines, such as Google, such that the optimizer machine learning model offers significant value to purchasable-unit distributors or manufacturers, which, in turn, may generate higher revenues to the store 102 owner or optimizer platform operator through increased sales of purchasable-units/products as described herein.
  • the output as generated by the optimizer machine learning model may be a user action score that defines a probability of the user to engage in a purchase associated with one or more purchasable-units/products as described herein.
  • the point-of- recognition optimizer servers 104 and/or 140 may then determine a plurality of competing purchasable-units based on the purchasable-unit ID, where the plurality of competing purchasable-units includes the recognized purchasable-unit and one or more additional purchasable-units.
  • the additional purchasable-units may be purchasable-units offered from offsite distributors, where the additional purchasable-units are offsite from the user’s current location.
  • the point-of-recognition optimizer servers 104 and/or 140 may then transmit, via a second computer transmission to the optimizer device, an offer for an offered purchasable-unit, where the offer originates from an outbidding purchasable-unit distributor.
  • the point-of-recognition system may receive feedback about purchase decision.
  • the feedback can include the number and prices about the purchasable-units that the consumer purchases.
  • the feedback can be used to update the user’s user-centric information profile as described herein.
  • processors may be temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions.
  • the modules referred to herein may, in some example embodiments, comprise processor- implemented modules.
  • the methods or routines described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or more processors or processor- implemented hardware modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location, while in other embodiments the processors may be distributed across a number of locations.

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Abstract

L'invention concerne des systèmes et des procédés destinés à un système d'optimisation de point de reconnaissance configurés pour optimiser des achats d'utilisateur sur site au niveau d'un emplacement physique. Selon divers aspects, un identifiant (ID) d'unité pouvant être achetée peut être reçu par l'intermédiaire d'une transmission informatique, l'ID d'unité pouvant être achetée, tel qu'identifié par un dispositif d'optimisation, étant associé à une unité pouvant être achetée reconnue, située sur site avec le dispositif d'optimisation. Sur la base de l'ID d'unité pouvant être achetée, une pluralité d'unités pouvant être achetées en compétition peuvent être identifiées, qui peuvent être des unités pouvant être achetées sur site ou hors site. Une offre pour une unité pouvant être achetée proposée est transmise par l'intermédiaire d'une seconde transmission informatique au dispositif d'optimisation, l'offre provenant d'un distributeur d'unités pouvant être achetées de surenchère, le distributeur d'unités pouvant être achetées de surenchère surenchérissant sur d'autres distributeurs d'unités pouvant être achetées en concurrence, chaque distributeur correspondant à la pluralité d'unités pouvant être achetées en concurrence, afin que le dispositif d'optimisation ait l'opportunité de recevoir l'offre.
PCT/US2019/025484 2018-04-13 2019-04-03 Systèmes et procédés concernant une optimisation de point de reconnaissance d'achats d'utilisateur sur site au niveau d'un emplacement physique Ceased WO2019199530A1 (fr)

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US15/953,187 US10062069B1 (en) 2017-06-29 2018-04-13 Systems and methods regarding point-of-recognition optimization of onsite user purchases at a physical location
US15/953,187 2018-04-13

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1895462A1 (fr) * 2006-08-31 2008-03-05 Accenture Global Services GmbH Architecture de marketing combinée et procédés de recherche et de ciblage correspondants utilisant de telles architectures
US20110145093A1 (en) * 2009-12-13 2011-06-16 AisleBuyer LLC Systems and methods for purchasing products from a retail establishment using a mobile device
US20130085888A1 (en) * 2011-09-29 2013-04-04 Samsung Electronics Co., Ltd. Method, apparatus and system for providing shopping service using integrating shopping cart
US20140324627A1 (en) * 2013-03-15 2014-10-30 Joe Haver Systems and methods involving proximity, mapping, indexing, mobile, advertising and/or other features
US9595062B2 (en) * 2012-10-12 2017-03-14 Wal-Mart Stores, Inc. Methods and systems for rendering an optimized route in accordance with GPS data and a shopping list

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1895462A1 (fr) * 2006-08-31 2008-03-05 Accenture Global Services GmbH Architecture de marketing combinée et procédés de recherche et de ciblage correspondants utilisant de telles architectures
US20110145093A1 (en) * 2009-12-13 2011-06-16 AisleBuyer LLC Systems and methods for purchasing products from a retail establishment using a mobile device
US20130085888A1 (en) * 2011-09-29 2013-04-04 Samsung Electronics Co., Ltd. Method, apparatus and system for providing shopping service using integrating shopping cart
US9595062B2 (en) * 2012-10-12 2017-03-14 Wal-Mart Stores, Inc. Methods and systems for rendering an optimized route in accordance with GPS data and a shopping list
US20140324627A1 (en) * 2013-03-15 2014-10-30 Joe Haver Systems and methods involving proximity, mapping, indexing, mobile, advertising and/or other features

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