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WO2013009660A1 - Appareils, procédés et systèmes de plate-forme d'incitation ciblée et à notifications réduisant la largeur de bande bidirectionnelle - Google Patents

Appareils, procédés et systèmes de plate-forme d'incitation ciblée et à notifications réduisant la largeur de bande bidirectionnelle Download PDF

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Publication number
WO2013009660A1
WO2013009660A1 PCT/US2012/045875 US2012045875W WO2013009660A1 WO 2013009660 A1 WO2013009660 A1 WO 2013009660A1 US 2012045875 W US2012045875 W US 2012045875W WO 2013009660 A1 WO2013009660 A1 WO 2013009660A1
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WO
WIPO (PCT)
Prior art keywords
consumer
user
product
merchant
data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/US2012/045875
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English (en)
Inventor
Vish SHASTRY
Marc Blum
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Visa International Service Association
Original Assignee
Visa International Service Association
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US13/520,481 external-priority patent/US10223691B2/en
Priority claimed from US13/542,443 external-priority patent/US10121129B2/en
Application filed by Visa International Service Association filed Critical Visa International Service Association
Publication of WO2013009660A1 publication Critical patent/WO2013009660A1/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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241—Advertisements
    • G06Q30/0251—Targeted advertisements
    • G06Q30/0261—Targeted advertisements based on user location
    • 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
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/384—Payment protocols; Details thereof using social networks
    • 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
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/387—Payment using discounts or coupons
    • 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
    • G06Q30/0241—Advertisements

Definitions

  • PCT application no. PCT/US12/26205 is also a continuation-in-part of,
  • the present innovations generally address apparatuses, methods, and systems for online advertising, and more particularly, include BIDIRECTIONAL BANDWIDTH REDUCING NOTIFICATIONS AND TARGETED INCENTIVE PLATFORM APPARATUSES, METHODS AND SYSTEMS ("Ad-Track").
  • FIGURES lA-C show block diagrams illustrating example aspects of the Ad-Track
  • FIGURES 2A-2B show a block diagram illustrating data flows between Ad- Track affiliated entities within embodiments of Ad-Track
  • FIGURES 3A-3B provide logic flow diagrams illustrating consumer tracking within embodiments of the Ad-Track
  • FIGURES 4A-4C provide logic flow diagrams illustrating consumer tracking heuristics analysis within embodiments of the Ad-Track
  • FIGURES 5A-5E provide exemplary user interface diagrams illustrating example aspects of the Ad-Track
  • FIGURES 6A-E show user interface and logic flow diagrams illustrating example aspects of virtual store injection
  • FIGURE 9 shows a block diagram illustrating example aspects of a centralized personal information platform in some embodiments of the Ad-Track;
  • FIGURES 10A-F show block diagrams illustrating example aspects of data models within a centralized personal information platform in some embodiments of the Ad-Track;
  • FIGURE 11 shows a block diagram illustrating example Ad-Track component configurations in some embodiments of the Ad-Track;
  • FIGURE 12 shows a data flow diagram illustrating an example search result aggregation procedure in some embodiments of the Ad-Track
  • FIGURE 13 shows a logic flow diagram illustrating example aspects of aggregating search results in some embodiments of the Ad-Track, e.g., a Search Results Aggregation ("SRA") component 1300;
  • FIGURES 14A-D show data flow diagrams illustrating an example card- based transaction execution procedure in some embodiments of the Ad-Track;
  • FIGURES 15A-E show logic flow diagrams illustrating example aspects of card-based transaction execution, resulting in generation of card-based transaction data and service usage data, in some embodiments of the Ad-Track, e.g., a Card-Based Transaction Execution ("CTE") component 1500;
  • FIGURE 16 shows a data flow diagram illustrating an example procedure to aggregate card-based transaction data in some embodiments of the Ad-Track;
  • FIGURE 17 shows a logic flow diagram illustrating example aspects of aggregating card-based transaction data in some embodiments of the Ad-Track, e.g.,
  • FIGURE 19 shows a logic flow diagram illustrating example aspects of aggregating social data in some embodiments of the Ad-Track, e.g., a Social Data Aggregation (“SDA") component 1900;
  • FIGURE 20 shows a data flow diagram illustrating an example procedure for enrollment in value-add services in some embodiments of the Ad-Track;
  • FIGURE 21 shows a logic flow diagram illustrating example aspects of social network payment authentication enrollment in some embodiments of the Ad- Track, e.g., a Value-Add Service Enrollment ("VASE”) component 2100;
  • FIGURES 22A-B show flow diagrams illustrating example aspects of normalizing aggregated search, enrolled, service usage, transaction and/or other aggregated data into a standardized data format in some embodiments of the Ad-Track, e.g., a Aggregated Data Record Normalization (“ADRN”) component 2200;
  • ADRN Aggregated Data Record Normalization
  • FIGURE 23 shows a logic flow diagram illustrating example aspects of aggregating social data in some embodiments of
  • FIGURE 38 shows a datagraph diagram illustrating example aspects of transforming a user checkout request input via a User Purchase Checkout (“UPC”) component into a checkout data display output;
  • FIGURE 39 shows a logic flow diagram illustrating example aspects of transforming a user checkout request input via a User Purchase Checkout (“UPC") component into a checkout data display;
  • FIGURES 40A-B show datagraph diagrams illustrating example aspects of transforming a user virtual wallet access input via a Purchase Transaction Authorization (“PTA”) component into a purchase transaction receipt notification;
  • FIGURES 41A-B show logic flow diagrams illustrating example aspects of transforming a user virtual wallet access input via a Purchase Transaction Authorization (“PTA”) component into a purchase transaction receipt notification;
  • FIGURES 42A-B show datagraph diagrams illustrating example aspects of transforming a merchant transaction batch data query via a Purchase Transaction Clearance (“PTC”) component into an updated payment ledger record;
  • PTC Purchase Transaction Clearance
  • FIGURE 44 shows a block diagram illustrating example aspects of a Ad- Track controller.
  • FIGURE 44 shows a block diagram illustrating example aspects of a Ad- Track controller.
  • the leading number of each reference number within the drawings indicates the figure in which that reference number is introduced and/or detailed. As such, a detailed discussion of reference number 101 would be found and/or introduced in Figure 1.
  • Reference number 201 is introduced in Figure 2, etc. DETAILED DESCRIPTION
  • Ad-Track provides an advertising tracking and payment platform which combines online tracking of consumer behaviors and merchant advertising into purchase data.
  • Ad-Track may assist advertisers (e.g., merchants, etc.) close the loop between online/offline advertising and consumer's purchases while creating an incentive model for all participants.
  • Integration of an electronic wallet, a desktop application, a plug -in to existing applications, a standalone mobile application, a web based application, a smart prepaid card, and/or the like in capturing payment transaction related objects such as purchase labels, payment cards, barcodes, receipts, and/or the like reduces the number of network transactions and messages that fulfill a transaction payment initiation and procurement of payment information (e.g., a user and/or a merchant does not need to show an advertisement in the print media or obtain and send digital images of paper bills, hand in a physical payment card to a cashier, etc., to initiate a payment transaction, fund transfer, and/or the like).
  • the Ad-Track may provide customized advertisements to consumers, which reduces the volume of network communication messages of ads, and thus saves the network bandwidth usage, and improves ad network transmission efficiency and data communication latency performance.
  • a mobile wallet platform e.g., see FIGURES 31-40B
  • a digital/electronic wallet e.g., a digital/electronic wallet, a smart/prepaid card linked to a user's various payment accounts, and/or other payment platforms are contemplated embodiments as well; as such, subset and superset features and data sets of each or a combination of the aforementioned payment platforms (e.g., see FIGURES 31-40B) may be accessed, modified, provided, stored, etc. via cloud/server services and a number of varying client devices throughout the instant specification.
  • mobile wallet user interface elements are depicted, alternative and/or complementary user interfaces are also contemplated including: desktop applications, plug-ins to existing applications, stand alone mobile applications, web based applications (e.g., applications with web objects/frames, HTML 5 applications/wrappers, web pages, etc.), and other interfaces are contemplated.
  • desktop applications plug-ins to existing applications
  • stand alone mobile applications web based applications (e.g., applications with web objects/frames, HTML 5 applications/wrappers, web pages, etc.), and other interfaces are contemplated.
  • web based applications e.g., applications with web objects/frames, HTML 5 applications/wrappers, web pages, etc.
  • the Ad-Track payment processing component may be integrated with an digital/electronic wallet (e.g., a Visa V- Wallet, etc.), comprise a separate stand alone component instantiated on a user device, comprise a server/cloud accessed component, be loaded on a smart/prepaid card that can be substantiated at a PoS terminal, an ATM, a kiosk, etc., which may be accessed through a physical card proxy, and/or the like.
  • the Ad- Track may provide a merchant configuration UI for a merchant to create a campaign, set ad revenue sharing rules, and/or the like.
  • FIGURE lA provides an example block diagram illustrating Ad-purchase correlation within embodiments of the Ad-Track.
  • the a consumer "John Smith" 102 may view an advertisement 103 featuring a product, e.g., a laptop, etc., via an advertisement channel 105, e.g., a new website, etc.
  • the consumer "John Smith" 102 may purchase the featured product 108, e.g., at a merchant computer store 150, by submitting his payment information 107 to the point of sale (POS) terminal at the merchant store.
  • the consumer's credit card purchasing history may reflect the purchase of the laptop product.
  • the Ad-Track server 120 may determine whether the consumer's purchase of the advertised product 108 should be attributed to the advertisement 103 exposure. For example, if the Ad-Track server 120 reviews the consumer's purchasing history 112 and determines that the consumer has never shopped any product with the featured brand 114, the Ad-Track server 120 may correlate the purchase with the advertisement exposure. For example, the Ad-Track server 120 may distribute a contingent advertisement fee 116 to the advertisement 1 channel 105, wherein the advertisement fee is provided by the merchant as part of
  • FIGURE lB provides an example block diagram illustrating tracking
  • FIGURE lA may walk into a computer
  • such in-person interaction 116 including exposure to
  • the Ad-Track may track such in-store
  • consumer's mobile wallet 101 may track
  • the store injection component 117 may
  • Ad-Track server 120 19 subsequent purchase, e.g., via an Internet shopping site 122, the Ad-Track server 120
  • the 20 may generate heuristics that the purchase is a result of the in-store advertisement and
  • the Ad-Track server 120 may then distribute a contingent ad fee 116 to the
  • FIGURE lC provides an example block diagram illustrating
  • the Ad-Track may obtain a purchase
  • the Ad-Track server 120 may be any suitable payment network/issuer (e.g., Visa, etc.) and/or the like.
  • the Ad-Track server 120 may be any suitable payment network/issuer (e.g., Visa, etc.) and/or the like.
  • the Ad-Track server 120 may be any suitable payment network/issuer (e.g., Visa, etc.) and/or the like.
  • 29 patterns to provide individualized advertisement delivery. For example, if the consumer
  • the Ad-Track server 120 may based on heuristics 1 134 that it is unlikely the consumer may be interested in shopping for another plasma
  • the Ad-Track server may be integrated with an Ad
  • Track server may comprise an independent server that will feed information to the ad
  • network server 180 as to what ads to be provided to the consumer.
  • the ad the ad
  • network server 180 may receive instructions to generate predictive ads 135 that does not
  • the Ad-Track server may instead feature TV
  • the electronics store may not provide ads of2 plasma TVs but the complementary gaming gadgets to the consumer.
  • FIGURE 2A shows a block diagram illustrating data flows between Ad-4 Track server and affiliated entities within various embodiments of the Ad-Track.
  • one or more consumers 202, Ad-Track server 220, Ad-Track6 database(s) 219, merchant 250, and/or advertising channels 230 are shown to interact7 via various communication network 213.
  • a consumer 202 may operate a wide variety of9 different user devices, including communications devices and technologies within0 embodiments of Ad-Track operation.
  • the consumer1 devices may include, but are not limited to, computer terminals, work stations, cellular2 telephony handsets, smart phones, tablets, personal digital assistants (PDAs), and/or3 the like.
  • the Ad-Track server 220 may be equipped at a terminal4 computer of the consumer 202.
  • the Ad-Track component may be5 instantiated on a consumer device to conduct Ad-Track analysis.
  • the Ad-Track server 220 may be a remote server which is accessed by the7 consumer 202 via a communication network 213, such as, but not limited to local area8 network (LAN), in-house intranet, the Internet, and/or the like.
  • a communication network 213 such as, but not limited to local area8 network (LAN), in-house intranet, the Internet, and/or the like.
  • the consumer 202 may be associated with an0 electronic wallet 203, which may have various registered accounts, including one or more bank accounts, an Ad-Track service account, a merchant membership account, and/or the like, possessed with the consumer 202.
  • a consumer may possess an electronic wallet linked a Bank of America checking account, a Chase credit card account, a Sam's Club membership account, and/or the like.
  • the consumer's electronic wallet may be registered for the Ad-Track service.
  • a consumer may operate a mobile device to access his electronic wallet to make a purchase, as further illustrated in the example screen shots in FIGURES 31- 43 ⁇
  • the consumer's electronic wallet may be registered with the Ad-Track server 220.
  • the consumer's electronic wallet may comprise a tag indicating the consumer electronic wallet is "Ad-Track enabled.”
  • a personal device e.g., a laptop, a smart phone, etc.
  • the browser may state information of the session indicating the session is eligible for Ad-Track service.
  • the user's browser may contain cookies of an Ad-Track label, and may notify the Google server of such Ad-Track label; the search engine may return a list of Ad-Track featured search results, e.g., listing the Ad-Track participating merchants' products/advertisements on top of the list, as shown in one example in FIGURE 4A.
  • the consumer may obtain advertising information 208 from the merchants' advertising channels 230, e.g., the Internet, etc.
  • the consumer 202 may click on a URL link and view an online advertisement 208 from an advertising channel 230, such as a news site, a social media ad, and/or the like.
  • an advertising channel 230 such as a news site, a social media ad, and/or the like.
  • the consumer's activities 215 may be recorded and forwarded to the Ad-Track server 220.
  • the Ad- Track server may run a Java applet within the consumer's browser and monitor the consumer's interactive activities with the displayed advertisement, e.g., clicking on the advertisement link, visiting a merchant website following links provided in the advertisement, making a subsequent purchase on the merchant website, and/or the like.
  • the Ad-Track server 220 may store the consumer activity information, and correlate it with subsequently received purchasing information to determine whether the consumer's purchase is triggered by the advertisement, as further illustrated in FIGURES 3A-3C.
  • the consumer device may provide a consumer activity message 215 to the Ad-Track server 220 as a HTTP(S) POST message including XML-formatted data.
  • a consumer activity message 215, substantially in the form of a HTTP(S) POST message including XML-formatted data, is provided below:
  • the consumer activity message 215 includes a consumer Google search event for "men sweater,” and the consumer subsequently clicked on two advertisement links returned in the search results, e.g., the "Banana Republic” and "Armani Exchange,” and the consumer's interactions with the advertisements, e.g., click and view, or just click through, etc., and the duration that the consumer has stayed on the advertisement are recorded and included in the consumer activity message 215.
  • the Ad-Track may track consumer advertisement exposure via In -Store injection data (e.g., see 600 in FIGURES 6C-6D) and web crawl via a profile aggregator (e.g., see the centralized personalized data file platform in FIGURE 11).
  • In -Store injection data e.g., see 600 in FIGURES 6C-6D
  • web crawl via a profile aggregator (e.g., see the centralized personalized data file platform in FIGURE 11).
  • the consumer may submit payment information to make a purchase request 224a with the merchant 250 (e.g., either at a physical merchant store, or an online shopping site, etc.) when the consumer is interested in the advertised products.
  • the consumer may visit a participating merchant store's website, a third party shopping website featuring the merchant's product (e.g., Amazon.com, Zappos.com, etc.) and/or visit product advertisement via social media (e.g., Facebook, Twitter, etc.), and/or the like, and may submit an online purchase request if a desired product by providing payment information, e.g., entering a credit card number, electronic wallet information, and/or the like.
  • payment information e.g., entering a credit card number, electronic wallet information, and/or the like.
  • the consumer may visit a merchant store and make an in-store purchase of the product.
  • the consumer 202 may provide his Ad-Track wallet information included in the payment request 224a to a merchant store 250 prior to his check-out.
  • the consumer may swipe an Ad-Track membership magstripe card at a POS terminal of the merchant store.
  • the consumer may operate a smart phone for registration with the POS via short messages.
  • the consumer may register with the merchant via bar code scan of the consumer's AD-Track membership card and/or the product.
  • the consumer may provide a purchase request 224a to the merchant server 250 as a HTTP(S) POST message including XML-formatted data.
  • HTTP(S) POST message including XML-formatted data.
  • the Ad-Track server 220 may obtain an indication of the user purchase from a purchase request 224b received from a merchant 220.
  • a payment network/issuer (e.g., Visa) 240 may receive and process the purchase request 224b from the merchant 250 and may provide a purchase confirmation 224c to the the Ad-Track server 220 as an indication of purchase transaction when the transaction is finished and cleared.
  • the purchase confirmation message 224c may include fields similar to that of the purchase request, including fields such as the product information, merchant information, a timestamp, 1 and/or the like.
  • the Ad-Track server 220 may determine whether
  • the Ad-Track may determine whether the
  • the Ad-Track may determine complementary products to the
  • the merchant 250 may determine whether an
  • Track server 220 may receive an indication of the purchase (e.g., via the consumer's
  • the merchant may provide
  • the merchant may provide an incentive rewards to
  • the consumer e.g., a rebate amount, etc., for using Ad-Track.
  • a rebate amount for using Ad-Track.
  • the merchant 250 may allocate 2% of the purchase price of the purchase as an incentive
  • the Ad-Track server credit the
  • 31 variety of incentive awards may be provided to the consumer, such as store points, coupons, sample gifts, and/or the like.
  • the merchant may provide affiliate payment to the Ad-Track server 220, which may re-distribute the affiliate payment to the consumer as incentive rewards, and affiliate payment to the advertising channels 230 for advertising fee.
  • the merchant may allocate 6% of the purchase price of a transaction to the Ad-Track server 220, and request 2% be re-distributed to an advertising channel (e.g., Google, etc.), and 2% be credited to the consumer.
  • an advertising channel e.g., Google, etc.
  • the Ad-Track server 220 may establish data records of registered consumers, merchants, past transactions 223 for storage in a database 219.
  • the consumer/merchant transaction record 223 may comprise information with regard to the purchase price, a purchase time-stamp, conditions of the purchase (e.g., whether eligible for Ad-Track affiliate payment), and/or the like.
  • an exemplary XML record of a transaction may take a form similar to the following:
  • the purchase includes a product from the merchant "Banana Republic," and the merchant may specify rules for the affiliate payment eligibility, e.g., a time frame of 280 days prior to the purchase, during which the consumer did not purchase any product of the same "category," e.g., Banana Republic men's apparel.
  • the merchant may expand the purchase range to the entire brand name, e.g., requiring a consumer with no prior purchase of any Banana Republic products within the past 280 days, etc.
  • the merchant may further specify that purchases made via a list of participating sites are eligible to be considered for affiliate payment, e.g., Amazon.com, etc.
  • the merchant may further specify the affiliate payment rule, e.g., splitting 2% of the purchase price to the Ad-Track, Google and the consumer, etc.
  • the Ad-Track server 220 may store the transaction record by issuing PHP/SQL commands to store the data to the database table (such as FIGURE 44, Transactions 44i3 ⁇ 4).
  • An example transaction record store command 223, substantially in the form of PHP/SQL commands, is provided below:
  • VALUES ($transaction_id$, $transaction_date$ , $requested_time$, $receipt_time$ , $user_id$, $user_name$, $user_password$, $account_no$ , $total_amount$, $transfer_log$, $payee_id$, $payor_id$, $transfer_amount$ ); //
  • a consumer data aggregator 270 may collect various consumer data from various sources (e.g., see 1101-1105 in FIGURE 11).
  • the consumer operating a mobile wallet 203 may obtain store injection data 255a from the merchant store, and forward 1 such injection data 255b indicating consumer activities in a physical merchant sore to
  • the consumer data aggregator 270 the consumer data aggregator 270.
  • the store injection data the store injection data
  • 3 255a-b may comprise the consumer's GPS location information, duration of the stay,
  • the mobile wallet 203 may provide an store injection data message 255b to
  • Ad-Track server as a HTTP(S) POST message including XML-formatted data.
  • HTTP(S) POST message including XML-formatted data is provided below:
  • the store injection data message 255b includes the GPS information of a physical "Banana Republic” store and indicates that the consumer "John Smith" has visited and stayed in the store for 56 minutes.
  • other store event types may reflect in-store ad exposure to the consumer, such as price checking, etc.
  • the store injection data message 255b comprise information of consumer's price check of a product using a mobile wallet.
  • the consumer may operate his/her mobile wallet device (e.g., a smartphone, etc.) to scan a QR code of the product (e.g., see 3516 in FIGURE 35A) and generate a price comparison check, e.g., the price listings on merchant sites "amazon.com” and "shop.com.” If the user has clicked on a searched merchant site, e.g., www.shop.com, such information is also fed to the consumer data aggregator 270, which may be considered as an ad exposure event. Further implementations of store injection data collection is illustrated in FIGURES 6A-6D.
  • the consumer data aggregator 270 may obtain social media feeds 256 from a social media platform 260.
  • a consumer's social payment e.g., see FIGURE 32D
  • social comments e.g., see FIGURE 32D
  • social comments e.g., see FIGURE 32D
  • social comments e.g., see FIGURE 32D
  • social comments e.g., see FIGURE 32D
  • social comments e.g., see FIGURE 32D
  • the social media platforms 260 may provide a social media feeds message 256 to the Ad-Track server as a HTTP(S) POST message including XML- formatted data.
  • a social media feeds message substantially in the form of a HTTP(S) POST message including XML-formatted data, is provided below: POST /social_feed.php HTTP/1.1
  • the consumer data aggregator 270 may obtain updates from web crawl 258 from various website 230, e.g., consumer's blog posts, browsing activities, etc.
  • the web server 230 may provide an update message 258 to the Ad-Track server as a HTTP(S) POST message including XML- formatted data.
  • An example listing of an web update message 258, substantially in the form of a HTTP(S) POST message including XML-formatted data, is provided below:
  • FIGURE 11 Further implementations of aggregating consumer related data from social media, web, and/or various internet resources are further illustrated in FIGURE 11.
  • the consumer data aggregator 270 may aggregate consumer ad exposure data 259, and store the aggregation results in a data store.
  • the Ad-Track server 220 may generate an ad exposure query 261 to the consumer data aggregator 270. For example, when the Ad-Track server 220 has received a purchase indication (e.g., see 224b in FIGURE 2A), the Ad-Track server 220 may query on the purchased item to determine whether the consumer has prior ad exposure for the purchased item.
  • the Ad-Track server 220 may issue PHP/SQL commands to query a database table (such as FIGURE 44, social 4419, web data 4419) for ad exposure data.
  • ad exposure data query 261 substantially in the form of PHP/SQL commands, is provided below:
  • $query "SELECT comment like access FROM SocialTable WHERE product LIKE ' 1 $Banana Republic” ;
  • the Ad-Track server may receive an ad exposure
  • the ad is prior ad exposure to the queries product name, or brand name. For example, the ad
  • exposure data 262 may comprise any previously stored ad exposure record in a form
  • the Ad-Track server 220 may then proceed to correlation at 227 in
  • FIGURES 3A-3B provide logic flow diagrams illustrating embodiments of
  • a consumer may submit consumer registration
  • the Ad-Track may run a remote
  • FIGURES 31-37B 21 FIGURES 31-37B.
  • a merchant e.g., a brand name product company
  • the merchant may submit a request to advertise to the Ad-
  • the Ad-Track may generate an advertising component for display at the
  • a consumer upon registration with Ad-Track, a consumer may
  • the consumer 1 may trigger an event which sends an indication to Ad-Track indicating the consumer is
  • the consumer's device may send a query to search network
  • HTTP POST message e.g., se
  • the triggered event may include, but not limited to0 consumer clicking on a search advertisement of "men's sweaters”, consumer clicking on1 a display advertisement of "men's sweaters,” consumer interacting with an2 advertisement related to "men's sweaters” for an extended period, consumer visiting a3 merchant website featuring "men's sweaters,” consumer visiting a product review4 website related to "men's sweaters,” and/or the like.
  • the Ad-Track may receive the event trigger and6 query for registered related merchants 320.
  • the Ad-8 Track may receive this indication that the consumer is interested in “men's sweaters,”9 and may form a query in its merchant database for merchants that offer “men's0 sweaters.” 1 [ 00102 ]
  • the Ad-Track may instantiate an advertisement2 component (e.g., on the browser, etc.) for a queried merchant 325.
  • the Ad-3 Track may determine "Banana Republic” offers “men's sweaters,” and may then display4 an advertisement for Banana Republic to the consumer.
  • the Ad-Track may sort a list of advertisements of different merchants7 based on a variety of metrics, such as, but not limited to relevancy, the percentage of8 affiliated payment the merchant is willing to pay Ad-Track, and/or the like.
  • the consumer may view the provided advertisement0 and submit an indication of view the advertisement to Ad-Track 330, e.g., by clicking on1 the advertisement.
  • the Ad-Track may store the indication 333, e.g., a time-stamp, an advertisement ID, a consumer ID, and/or the like.
  • the Ad-Track may operate as an ad network.
  • Ad-Track may communicate with an ad network, and otherwise shed such ad network features itself, and provide indication of transactions while performing operations as follows.
  • a consumer may subsequently make a purchase of the advertised product 335, e.g., a Banana Republic sweater for men as discussed in the above example.
  • the consumer may purchase the product via a variety of commercial channels, such as in-store, via the merchant website, via a shopping website (e.g., Amazon.com, macys.com, etc.), and/or the like.
  • information that used to confer an eligible product has been purchased by the consumer may be obtained from the user device (e.g., an electronic wallet on a mobile device, etc.), the merchant, an issuer and/or payment network cooperating with the Ad-Track system.
  • registered consumers may have all account transactions that occur with registered accounts serve as a trigger to determine if such purchased item are eligible for Ad-Track rewards.
  • a merchant may charge a consumer's payment account for the purchase, and the transaction may be processed by a payment network and/or an issuer (e.g., Visa, etc.).
  • the Ad-Track may be disposed with communication with the payment network/issuer, and thereby may be provided the payment indication through such networks (e.g., see 224b in FIGUER 2A).
  • the merchant may confirm purchase transaction with a payment network.
  • the Ad-Track may receive purchase confirmation 339 from the merchant, the payment network, and/or the like.
  • the merchant and the Ad-Track may determine whether the purchase is eligible for a merchant affiliate payment 340, e.g., whether the merchant should pay Ad-Track for advertising.
  • rules for determining the eligibility may be established in a merchant-Ad-Track agreement.
  • the Ad-Track has aggregated different types of consumer activities (e.g., 215 in FIGURE 2A; cookies, ad interception, click interception, search results 1101, transaction data 1 aggregation 1102, service usage data aggregation 1103, enrollment data aggregation
  • consumer activities e.g., 215 in FIGURE 2A; cookies, ad interception, click interception, search results 1101, transaction data 1 aggregation 1102, service usage data aggregation 1103, enrollment data aggregation
  • Ad-Track database and associated with a consumer identifier, and a timestamp at which
  • the consumer activity Ad-Track database may be used to determine whether the consumer activity Ad-Track database is used to calculate the activity.
  • such database may be queried on rules that establish eligibility for revenue sharing
  • Ad-Track 9 should pay a portion of the transaction amount to the Ad-Track.
  • the Ad-Track may generate a query into the correlation4 rule table (e.g., 44i9r in FIUGRE 44) to determine whether the purchase is correlated5 with the ad exposure:
  • the correlation rule may acknowledge a subsequent purchase as a result of1 ad exposure.
  • the Ad-Track may generate a query into the correlation rule2 table:
  • eligibility of the purchased item may be determined
  • the purchase takes place, e.g., online purchase, in-store purchase, and/or the like.
  • the merchant may through pay a portion
  • this payment may be variable based on the consumer's previous
  • Ad-Track may split the payment. For example, a portion of the payment
  • 24 portion of the payment (e.g., 1%) may be made to the consumer as an incentive for
  • Ad-Track may provide rewards as incentive
  • the Ad-Track rewards may be provided to the
  • 29 consumer in various ways. For example, a consumer may obtain cash back via his
  • FIGURE 5C For another example, a consumer may
  • FIGURE 3B provides a logic flow diagram illustrating store injection data aggregation within embodiments of the Ad-Track.
  • a consumer may start the process by walking into a merchant store 351.
  • the consumer may operate a mobile wallet and submit a check-in message to the consumer data aggregator via the wallet check-in component 352a.
  • the merchant may receive store injection request 352b, and provide merchant store information to aggregator via the mobile wallet.
  • the data aggregator may store the consumer location indication 354 from the check-in message and monitor further store injection data.
  • the aggregator may extract product/brand information 356 from the message, e.g., the consumer may operate the mobile wallet to scan a barcode of a product, price check and comparison, checkout at a merchant POS, etc.
  • the aggregator may determine whether there is an external URL 358a in the store injection message, e.g., the consumer may snap the barcode/QR code to conduct Internet search on the product, and/or conduct a price match which may direct the consumer to another URL.
  • the aggregator may generate and store the shop trail record 361 including the current merchant store, e.g., the store that consumer has walked in at 351. [ 00115 ] In another implementation, if the store injection event message includes an external link and the consumer click on the external link 358a, e.g., from the price match results, the aggregator may proceed to determine a type of the link, e.g., whether it is a store injection to a new store 358b.
  • the aggregator may store the external channel (e.g., "Newsdaily.com") 359 and proceed to 335.
  • the external link is a store injection 358b, e.g., the consumer may be directed to another online store (e.g., Amazon.com, buy.com, 1 etc.) 358b, the aggregator may include the new store into the shop trail 360, and
  • injected store merchant e.g., Amazon.com, buy.com, etc.
  • the aggregator may store the external channel 359 if it is visited by the
  • FIGURES 6A-6D 8 injection data aggregation are provided in FIGURES 6A-6D.
  • FIGURE 4A provides a logic flow diagram illustrating predictive
  • the Ad-Track 10 advertising within embodiments of the Ad-Track.
  • the Ad-Track
  • 11 may may collect various consume related activity data 404, e.g., store injection data
  • Track may generate consumer purchasing heuristics based on merchant rules 406. For
  • a merchant may specify a rule that if a consumer has purchased a digital
  • Ad-Track may establish rules and heuristics that if a
  • Ad-Track may perform data mining on consumer
  • a digital camera may have the propensity to purchase a camera bag, and may then
  • the Ad-Track may purge the complementary product
  • the Ad-Track when the Ad-Track receives a purchase confirmation that a consumer has purchased a plasma TV, the Ad-Track may perform the following query for ads featuring complementary products:
  • $query "SELECT ad_id, ad_name, ad_product_id, ad_data, ad_merchant_id, ad_template FROM AdsTable WHERE ad_complementary_product_id LIKE ' % ' "PlasmaTVOOl";
  • $result mysql_query ( $query) ; // perform the search query
  • the Ad-Track may query for any complementary products which are labeled as complementary to the purchased plasma TV.
  • the complementary products may include video gaming gadgets, a TV stand, and/or the like.
  • the Ad-Track may determine related advertisement based on the generated heuristics 413 at step 406.
  • the Ad-Track may receive a batch of triggers (e.g., transaction records, etc.), and may review and analyze each record 414 until there is no more triggers.
  • the Ad-Track may determine not to provide advertisements of similar products to the consumer within a period of time (e.g., 6 months, etc.), as consumer purchasing pattern may reflect that it is rare a consumer may consecutively purchase a plasma TV within 6 months.
  • a period of time e.g., 6 months, etc.
  • the consumer may interact with the ads 418, e.g., click-through, etc. Such activities may be captured by the aggregator for analysis.
  • FIGURES 4B-4C provides a logic flow illustrating correlating consumer 1 trigger activities and purchases in one embodiment of the Ad-Track.
  • Ad-Track upon Ad-Track receiving an indication that a registered consumer has
  • the Ad-Track may retrieve consumer
  • the Ad-Track may form a
  • the Ad-Track and/or the merchant may establish
  • the Ad-Track may require the purchased
  • Track and/or the merchant may have a more relaxed rule, e.g., as long as the consumer
  • Ad-Track may determine whether the ad has been "viewed" by the consumer 453, as the
  • the Ad-Track may
  • the Ad-Track may go
  • 27 may move on to determine an affiliate payment, e.g., based on consumer loyalty type
  • the Ad-Track may retrieve the consumer's purchasing
  • the merchant may issue
  • the Ad-Track may apply another rule
  • the merchant may provide 6% of the proceeds to Ad-
  • the merchant may not provide affiliate
  • Ad-Track may direct the data record for staff review 476 to determine
  • the Ad-Track may extract injection data content 477
  • the Ad-Track may determine whether the
  • 14 injection data message comprises any external link 478. If not, the Ad-Track may
  • 16 module 484 for correlation analysis e.g., whether the consumer's store check-in event
  • injection data 17 may be correlated with a subsequent purchase. Additional correlation rules may be is applied to store injection data. For example, if the injection data comprises any in-store
  • the Ad-Track may be 19 check-in, or scans (e.g., price check, product location inquiry, etc.).
  • the merchant may specify a price check at a
  • injection data comprises an external link
  • the Ad-Track may determine whether the
  • the Ad-Track may determine whether there is
  • 29 is a click-through, or whether the consumer makes a purchase transaction 480 via the
  • the Ad-Track may include the clicked
  • an injection data message may comprise information that a
  • the Ad-Track may
  • a merchant may establish rules that if the user has clicked on a price
  • the shopping site may not be considered as an eligible channel for ad revenue
  • the Ad-Track may determine whether the merchant (e.g., Amazon.com) has
  • FIGURES 8A-8C 19 implementations are discussed in FIGURES 8A-8C.
  • FIGURES 5A-5B provide example screen shots illustrating embodiments
  • a consumer may initiate a trigger, e.g., a Google search
  • the Ad-Track applet 525 running on the browser application may
  • Ad-Track may then send an Ad-Track advertisement 510 within the browser of the
  • Track component 525 may send an indication recording a "user click" to the Ad-Track
  • FIGURE 5B provides an alternative embodiment of providing Ad-Track
  • the Ad-Track component 525 may provide an advertisement via a floating window 550.
  • the Ad-Track component 525 may then monitor the consumer's interaction with the advertisement. For example, the consumer may immediately close the floating winder 550. For another example, the consumer may stay on the floating window and scroll the page to view the listed products 555, and the Ad-Track component 525 may record the time length the consumer stays on the window. For another example, the consumer may click on the picture to be redirected to the merchant site for more product details 560.
  • the Ad-Track may record these consumer activities and evaluate correlation with the consumer's subsequent purchase, as discussed in FIGURES 2A-2B.
  • Ad-Track may label the purchase and generate ads of complementary products to the consumer.
  • FIGURE 5D when the consumer enters the same search term "men's sweater,” as Ad- Track recognizes the consumer has purchased men's sweaters from the merchant brand "Banana Republic," the Ad-Track may provide ads of complementary products 565, e.g., men's accessories of the same brand, etc. .
  • FIGURE 5E provides a schematic mobile application screen shots within embodiments of the Ad-Track.
  • the consumer may operate a smart phone (e.g., an Apple iPhone, etc.) to browse an Ad-Track advertisement 510.
  • the consumer may make a purchase of the advertised product via his electronic wallet 585.
  • the mobile wallet application is further discussed in FIGURES 31-40B.
  • FIGURES 6A-C show user interface and logic flow diagrams illustrating example aspects of virtual store injection into a virtual wallet application in some embodiments of the Ad-Track.
  • the virtual wallet application may presents screens 600 and 610, respectively, as depicted in FIGURE 6A.
  • the virtual wallet application displays a list of merchants participating in the virtual wallet of the UEP, e.g., 601-605.
  • the virtual wallet application displays a list of merchants participating in the virtual wallet of the UEP and at or nearby the approximate location of the user the user.
  • the user may click on any of the merchants listed in the two screens 600 and 610, to be injected into the store inventory of the merchant. Upon injection, the user may be presented with a screen such as 620. Also, in some implementation, if a user clicks on any of the items listed on screen 620, the user may be taken to a screen 630.
  • the user may be injected into a virtual reality 2D/3D storefront of the merchant.
  • the user may be presented with a plan map view of the store 641.
  • the user may provided with the user's location (e.g., using GPS, or if not available, then using a coarse approximation using a cellular signal).
  • the locations of the user's prior and current purchases may be provided for the user, if the user wishes (see 642, the user can turn the indications off, in some implementations).
  • the user may be provided with a 3D aisle view of an aisle within the virtual storefront.
  • the user may point the view direction(s) at any of the objects to obtain virtual tools to obtain items from off the "virtual shelf," and place them in the user's virtual cart.
  • the screen at 650 shows an augmented reality view of an aisle, where user may see pins of items suggested by a concierge, or that were bookmarked in their cart/wishlist highlighted through a live video view 653.
  • the color of a pin depicted in the augmented reality view may be indicative of an attribute of the suggestion, e.g., a discount offer, a warning not to buy, a prior purchase, etc.
  • a color of a 3D viewer window may indicate additional attributes such as, without limitation, whether the product was recommended by the user's social graph, the product's rating (e.g., according to experts, the user's friends, Internet users, I etc.), and/or the like.
  • a virtual store aisle view (e.g., akin to a Google map
  • 3 Street View may be navigated 651 when the consumer is not at the store, but would like
  • the directional control 651 allows for navigation up and down the
  • FIGURE 6C shows a logic flow diagram illustrating example aspects of
  • VWSI Virtual Wallet Store Injection
  • a user may provide a user input into a user device executing a virtual
  • the user device may obtain the user input, e.g.,
  • the user input may include, but not be limited to:
  • buttons on a joystick/game console 16 depressing buttons on a joystick/game console, voice commands, single/multi-touch
  • the client may determine the type of user input, e.g.,
  • the client may determine whether the user input is one that requests
  • the user input constitutes a store injection request, e.g., 604, option "Yes," the client
  • the client may generate a store injection request message, e.g., 605.
  • the client may generate a store injection request message, e.g., 605.
  • the client may generate a store injection request message, e.g., 605.
  • the server may obtain the store injection request from the client, and may parse the message, e.g., 606.
  • the client may utilize a parser such as the example parsers discussed below in the description with reference to FIGURE 61.
  • the client may extract the request parameters from the client's message and generate a query for the requested store injection data, e.g., 607.
  • Examples of store injection data include, without limitation: product information, product images, product animations, videos, media content, animations, store wireframes, street view data, map data, lists of products (e.g., XML data), URLs pointing to other store injection data, augmented reality data, executable script (e.g., JavaScriptTM, Adobe Flash® object, .bundle files, HTML5 code, etc.), and/or the like.
  • the server may issue PHP/SQL commands to query a database table (such as FIGURE 44, Shop Sessions 44191) for store injection data.
  • An example store injection data query command substantially in the form of PHP/SQL commands, is provided below:
  • $query "SELECT product_information, product_images , product_animations, videos, media_content, animations, store_wireframes , street_view_data, map_data, product_list, pointer_URL_list, augmented_reality_data, executable_script_list FROM ShopSessionTable WHERE session_id LIKE '%' $sessionid" ;
  • $result mysql_query ( $query) ; // perform the search query mysql_close ( "Ad-Track_DB . SQL” ) ; // close database access
  • a database of the server may provide the data requested by the server, e.g., 608.
  • the server may generate a store injection response message, e.g., 609.
  • the server may provide a store injection response message to the client as a HTTP(S) POST message including XML-formatted data.
  • HTTP(S) POST message including XML-formatted data.
  • the client may obtain the store injection response message, and parse the message, e.g., 610.
  • the client may render a visualization of the virtual store using the extracted store injection data, e.g., 611, and display the rendered visualization for the user via a display device of the client, e.g., 612.
  • the user may provide a user input into the virtual store visualization generated by the client, e..g, 621.
  • the client may obtain the user input, e.g., 622, and may determine the type of input provided by the user into the client, e.g., 623.
  • the client may identify a product that the user desires to add to a shopping cart, e.g., 625, and may add the user-selected product to a virtual shopping cart or wishlist, e.g., 626.
  • the user input represents a store navigation request (e.g., walking through the aisle within a virtual store), e.g., 627, option "Yes”
  • the client may identify the store navigation action requested by the user, e.g., 628, and may generate a store injection request message for the server to process the user's store navigation request (see, e.g., 605-612).
  • the client may generate a card authorization request, e.g., 630, as a trigger for a purchase transaction, and may provide the card authorization request to a purchase transaction authorization component such as the example PTA component discussed in the description with reference to FIGURE 41A.
  • a purchase transaction authorization component such as the example PTA component discussed in the description with reference to FIGURE 41A.
  • the user may view details of the item designed to facilitate the user to purchase the item at the best possible terms for the user.
  • the virtual wallet application may provide a detailed view of the item at the point where it was snapped by the user using the user device, 671, including an item description, price, merchant name, etc.
  • the view may also provide a QR code 672, which the user may tap to save to the wallet for later use, or to show to other users who may snap the QR code to purchase the item.
  • the view may provide additional services for the user, including but not limited to: concierge service; shipment services, helpline, and/or the like, 673.
  • the view may provide prices from competing merchants locally or on the web, 674. Such pricing data may be facilitated by the centralized personal information platform components described further below in the discussion with reference to FIGURES 11-30.
  • the view may provide the user with the option to (see 675): store the snapped code for later, start over and generate a new code, turn on or off a GPS tagging feature, use a previously snapped QR code, enter keywords associated with the QR code, associated the items related to the QR code to an object, and/or the like.
  • the virtual wallet may provide a SmartBuy targeted shopping feature. For example, the user may set a target price 676 for the product 671 that the user wishes to buy. The virtual wallet may provide a real-time market watch status update 677 for the product. When the market price available for the user falls below the user's target price 676, the virtual wallet may automatically buy the product for the user, and provide a shipment/notification to the user. The user may at any time add the item to one of the user's carts or wishlists (see 678).
  • the user may view the details of the items 682 and the amount(s) of each item, the merchant, etc., 682.
  • the user may be able to perform additional operations in this view. For example, the user may (re)buy the item 683, obtain third-party reviews of the item, and write reviews of the item 684, add a photo to the item so as to organize information related to the item along with the item 685, add the item to a group of related items (e.g., a household), provide ratings 687, or view quick ratings from the user's friends or from the web at large.
  • a group of related items e.g., a household
  • Such systems may be implemented using the example centralized personal information platform components described below in the discussion with reference to FIGURES 11-30.
  • the user may add a photo to the transaction.
  • a post including the photo may be generated and sent to the social channels for publishing.
  • any sharing may be optional, and the user, who did not share the purchase via social channels, may still share the photo through one or more social channels of his or her choice directly from the history mode of the wallet application.
  • the user may add the transaction to a group such as company expense, home expense, travel expense or other categories set up by the user.
  • Such grouping may facilitate year-end accounting of expenses, submission of work expense reports, submission for value added tax (VAT) refunds, personal expenses, and/or the like.
  • the user may buy one or more items purchased in the transaction. The user may then execute a transaction without going to the merchant catalog or site to find the items. In a further implementation, the user may also cart one or more items in the transaction for later purchase.
  • the history mode in another embodiment, may offer facilities for obtaining and displaying ratings 687 of the items in the transaction. The source of the ratings may be the user, the user's friends (e.g., from social channels, contacts, etc.), reviews aggregated from the web, and/or the like.
  • the user interface in some implementations may also allow the user to post messages to other users of social channels (e.g., TWITTER or FACEBOOK).
  • the display area 688 shows FACEBOOK message exchanges between two users.
  • a user may share a link via a message 689. Selection of such a message having embedded link to a product may allow the user to view a description of the product and/or purchase the product directly from the history mode. [o o i48 ]
  • the wallet application may display a shop trail for the user, e.g., 690.
  • a user may have reviewed a product at a number of websites (e.g., ElecReports, APPL FanBoys, Gizmo, Bing, Amazon, Visa Smartbuy feature (e.g., that checks various sources automatically for the best price available according to the user preferences, and provides the offer to the user), etc.), which may have led the user to a final merchant website where the user finally bought the product.
  • the Ad-Track may identify the websites that the user visited, that contributed to the user deciding to buy the product, and may reward them with a share of the revenues obtained by the "point-of-sale" website for having contributed to the user going to the point-of-sale website and purchasing the product there.
  • the websites may have agreements with product manufacturers, wholesalers, retail outlets, payment service providers, payment networks, amongst themselves, and/or the like with regard to product placement, advertising, user redirection and/or the like.
  • the Ad-Track may calculate a revenue share for each of the websites in the user's shopping trail using a revenue sharing model, and provide revenue sharing for the websites.
  • the virtual wallet may provide a SmartBuy targeted shopping feature.
  • the user may set a target price 691 for the product 682 that the user wishes to buy.
  • the virtual wallet may provide a real-time market watch status update 692 for the product.
  • FIGURES 7A-C show user interface diagrams illustrating example aspects of a discovery shopping mode of a virtual wallet application in some embodiments of the Ad-Track.
  • the virtual wallet application may provide a 'discovery shopping' mode for the user.
  • the virtual wallet application may obtain information on aggregate purchasing behavior of a sample of a population relevant to the user, and may provide statistical/aggregate information on the purchasing behavior for the user as a guide to facilitate the user's shopping.
  • the discovery shopping mode 701 may provide a view of aggregate
  • the virtual wallet application may provide visualization
  • the virtual wallet application may also provide an indicator
  • the user may be able to visualize the differences between the user's1 purchasing behavior and consumer behavior in the aggregate.
  • the user may be able to2 turn off the user's purchasing behavior indicator (see 710).
  • the3 virtual wallet application may allow the user to zoom in to and out of the visualization,4 so that the user may obtain a view with the appropriate amount of granularity as per the5 user's desire (see 707-308).
  • the user may be able to reset the visualization6 to a default perspective (see 711).
  • the discovery shopping mode 721 may provide a view of8 aggregate consumer response to opinions of experts, divided based on opinions of9 experts aggregated form across the web (see 702).
  • the centralized0 personal information platform components described below in the discussion with1 reference to FIGURES 9-30 may facilitate providing such data for the virtual wallet2 application.
  • the virtual wallet application may provide visualizations of how well3 consumers tend to agree with various expert opinion on various product categories, and4 whose opinions matter to consumers in the aggregate (see 723-326).
  • the virtual wallet application may also provide an indicator (see 729) of6 the relative expenditure of the user of the virtual wallet application (see blue bars); thus7 the user may be able to visualize the differences between the user's purchasing behavior8 and consumer behavior in the aggregate. The user may be able to turn off the user's9 purchasing behavior indicator (see 730).
  • the virtual wallet0 application may allow the user to zoom in to and out of the visualization, so that the user1 may obtain a view with the appropriate amount of granularity as per the user's desire (see 727-328). At any time, the user may be able to reset the visualization to a default perspective (see 731).
  • the virtual wallet application may allow users to create targeted shopping rules for purchasing (see FIGURE 7A, 712, 722).
  • the user may utilize the consumer aggregate behavior and the expert opinion data to craft rules on when to initiate purchases automatically.
  • rule 741 specifies that the virtual wallet should sell the users iPad2 if its consumer reports rating falls below 7.75/5.0, before March 1, provided a sale price of $399 can be obtained.
  • rule 742 specifies that the virtual wallet should buy an iPad3 if rule 741 succeeds before February 15.
  • rule 743 specifies that the wallet should buy a Moto Droid Razr from the Android Market for less than $349.99 if its Slashdot rating is greater than 7.75 before February 1.
  • numerous rules with a wide variety of variations and dependencies may be generated for targeted shopping in the discovery mode.
  • the virtual wallet user may allow the user to modify a rule.
  • the wallet may provide the user with an interface similar to 746 or 747. The user may utilize tools available in the rule editor toolbox to design the rule according to the user's desires.
  • the wallet may also provide a market status for the items that are subject to the targeted shopping rules.
  • the virtual wallet application may provide a market watch feature, wherein the trends associated with items subject to targeted shopping rules may be tracked and visually represented for the user.
  • the visualization may take, in some implementations, the form of a ticker table, wherein against each item 75i(A)-(E) are listed a product category or cluster of expert opinions to which the product is related 752, pricing indicators, including, but not limited to: price at the time of rule creation 752, price at the time of viewing the market watch screen 753, and a target price for the items (A)-(E).
  • the market watch screen may provide a trending symbol (e.g., up, down, no change, etc.) for each item that is subject to a targeted shopping rule. Where an item satisfied the targeted rule (see item (E)), the virtual wallet may automatically initiate a purchase transaction for that item once the target price is satisfied.
  • FIGURES 8A-C show user interface and logic flow diagrams illustrating
  • a user may select the history mode
  • the wallet application may query the storage areas in the mobile device or
  • the user interface may then display the results of the query such as
  • the user interface may identify 804: a type of the transaction (e.g.,
  • any displayed transaction, coupon, bill, etc. may be added to a
  • the user may select a transaction, for example is transaction 806, to view the details of the transaction.
  • a transaction for example is transaction 806, to view the details of the transaction.
  • the user may view
  • the user may be able to perform
  • the user may (re)buy the item 813,
  • the item to a group of related items (e.g., a household), provide ratings 817, or view
  • 26 systems may be implemented using the example centralized personal information
  • the user may add a photo to the transaction. In a further implementation, if the user
  • a post including the photo may be
  • any combination thereof generated and sent to the social channels for publishing.
  • any combination thereof any combination thereof
  • 31 sharing may be optional, and the user, who did not share the purchase via social channels, may still share the photo through one or more social channels of his or her choice directly from the history mode of the wallet application.
  • the user may add the transaction to a group such as company expense, home expense, travel expense or other categories set up by the user. Such grouping may facilitate year-end accounting of expenses, submission of work expense reports, submission for value added tax (VAT) refunds, personal expenses, and/or the like.
  • the user may buy one or more items purchased in the transaction. The user may then execute a transaction without going to the merchant catalog or site to find the items.
  • the user may also cart one or more items in the transaction for later purchase.
  • the history mode may offer facilities for obtaining and displaying ratings 817 of the items in the transaction.
  • the source of the ratings may be the user, the user's friends (e.g., from social channels, contacts, etc.), reviews aggregated from the web, and/or the like.
  • the user interface in some implementations may also allow the user to post messages to other users of social channels (e.g., TWITTER or FACEBOOK).
  • the display area 818 shows FACEBOOK message exchanges between two users.
  • a user may share a link via a message 819. Selection of such a message having embedded link to a product may allow the user to view a description of the product and/or purchase the product directly from the history mode.
  • the wallet application may display a shop trail for the user, e.g., 820.
  • a user may have reviewed a product at a number of websites (e.g., ElecReports, APPL FanBoys, Gizmo, Bing, Amazon, Visa Smartbuy feature (e.g., that checks various sources automatically for the best price available according to the user preferences, and provides the offer to the user), etc.), which may have led the user to a final merchant website where the user finally bought the product.
  • a shop trail for the user e.g., 820.
  • websites e.g., ElecReports, APPL FanBoys, Gizmo, Bing, Amazon, Visa Smartbuy feature (e.g., that checks various sources automatically for the best price available according to the user preferences, and provides the offer to the user), etc.
  • the Ad-Track may identify the websites that the user visited, that contributed to the user deciding to buy the product, and may reward them with a share of the revenues obtained by the "point-of-sale" website for having contributed to the user going to the point-of-sale website and purchasing the product there.
  • the websites may have agreements with product manufacturers, wholesalers, retail outlets, payment service providers, payment networks, amongst themselves, and/or the like with regard to product placement, advertising, user redirection and/or the like.
  • the Ad-Track may calculate a revenue share for each of the websites in the user's shopping trail using a revenue sharing model, and provide revenue sharing for the websites.
  • the virtual wallet may provide a SmartBuy targeted shopping feature.
  • the user may set a target price 821 for the product 812 that the user wishes to buy.
  • the virtual wallet may provide a real-time market watch status update 822 for the product.
  • the virtual wallet may automatically buy the product for the user, and provide a shipment/notification to the user.
  • FIGURE 8B shows a logic flow diagram illustrating example aspects of generating a virtual wallet user shopping trail in some embodiments of the Ad-Track, e.g., a User Shopping Trail Generation ("USTG”) component 800.
  • USTG User Shopping Trail Generation
  • a user device of a user may track the shopping activities of a user for later retrieval and/or analysis.
  • the device may obtain a user's input, 801, and determine a type of user input, 802. If the user engages in either browsing activity at a website of a merchant, or is navigating between websites (e.g., sometime when 803, option "No"), the device may track such activities. For example, the device may determine that the user's input is a navigational input (1104, option "Yes").
  • the device may stop a timer associated with the current URL (e.g., of a merchant such as amazon.com, ebay.com, newegg.com, etc., or a review website such as shlashdot.org, cnet.com, etc.) that the user is located at, and determine a time count that the user spent at the URL, 808.
  • the device may update a shop trail database (e.g., a local database, a cloud database, etc.) with the time count for the current URL, 809.
  • the device may also identify a redirect URL to which the user will be navigating as a result of the user's navigation input, 810.
  • the device may set the redict URL as the current URL, and reset activity and time counters for the current URL.
  • the device may generate a new entry in the shop trail database for the URL that has been made current by the user's navigational input, 811. [ 00160 ] If the user engaged in browsing activity at a current URL (1105, option "Yes"), the device may identify the URL associated with the browsing activity (e.g., if the browsing can be performed on the device across multiple windows or tabs, etc.). The device may increment an activity counter to determine a level of user activity of the user at the URL where the browsing activity is occurring, 806. The device may update the shop trail database with the activity count for the URL, 807.
  • the device may set the current URL as the "point-of- sale” URL (e.g., the merchant at which the user finally bought the product - e.g., amazon.com), 812.
  • the device may stop the time for the current URL, and update the shop trail database for the current URL, 813.
  • the device may generate a card authorization request to initiate the purchase transaction, 814, and provide the card authorization request for transaction processing (see, e.g., PTA 5700 component described below in the discussion with reference to FIGURE 57A-B).
  • the device may also invoke a revenue sharing component, such as the example STRS 820 component described below in the discussion with reference to FIGURE 8C.
  • FIGURE 8C shows a logic flow diagram illustrating example aspects of implementing a user shopping trail-based revenue sharing model in some embodiments of the Ad-Track, e.g., a Shopping Trail Revenue Sharing ("STRS”) component 820.
  • STS Shopping Trail Revenue Sharing
  • a user may have reviewed a product at a number of websites, which may have led the user to a final merchant website where the user finally bought the product.
  • the Ad-Track may identify the websites that the user visited, that contributed to the user deciding to buy the product, and may reward them with a share of the revenues obtained by the "point-of-sale" website for having contributed to the user going to the point-of-sale website and purchasing the product there.
  • the websites may have agreements with product manufacturers, wholesalers, retail outlets, payment service providers, payment networks, amongst themselves, and/or the like with regard to product placement, advertising, user redirection and/or the like.
  • a server may have stored a table of revenue sharing ratios, that provides a predetermined revenue sharing scheme according to which contributing websites will receive revenue for the user's purchase.
  • a server may obtain a list of URLs included in a suer's shopping trail, and their associated activity and time counts, 821.
  • the server may identify a point-of-sale URL where the user made the purchase for which revenue is being shared among the URLs in the shopping trail, 822.
  • the server may calculate a total activity count, and a total time count, by summing up activity and time counts, respectively, of all the URLs in the user's shopping trail, 823.
  • the server may calculate activity and time ratios of each of the URLs, 824.
  • the server may obtain a rvenue sharing model (e.g., a database table/matrix of weighting values) for converting activity and time ratios for each URL into a revenue ratio for that URL, 825.
  • the server may calculate a revenue share, 826, for each of the URLs in the user's shopping trail using the revenue sharing model and the revenue ratios calculated for each URL.
  • the server may provide a notification of the revenue for each URL (e.g., to each of the URLs and/or the point-of-sale URL from whom revenue will be obtained to pay the revenue shares of the other URLs in the user's shopping trail), 827.
  • FIGURE 9 shows a block diagram illustrating example aspects of a centralized personal information platform in some embodiments of the Ad-Track.
  • originators 911 such as merchants 911b, consumers 911c, account issuers, acquirers 911a, and/or the like, desire to utilize information from payment network systems for enabling various features for consumers.
  • Such features may include application services 912 such as alerts 912a, offers 912c, money transfers 912 ⁇ , fraud detection 912b, and/or the like.
  • such originators may request data to enable application services from a common, secure, centralized information platform including a consolidated, cross-entity profile-graph database 901.
  • the originators may submit complex queries to the Ad- Track in a structure format, such as the example below.
  • the query includes a query to determine a location (e.g., of a user), determine the weather associated with the location, perform analyses on the weather data, and provide exploded graphical view of the results of the analysis:
  • meta_data . / fModels/ robotExample .meta
  • tumblar_location . / fModels/robotExample . tumblar . location
  • a non-limiting, example listing of data that the Ad-Track may return based on a query is provided below.
  • a user may log into a website via a computing device.
  • the computing device may provide a IP address, and a timestamp to the Ad-Track.
  • the Ad-Track may identify a profile of the user from its database, and based on the profile, return potential merchants for offers or coupons: Use Case 3
  • Test case 2 IP 148 : 181 : 75 Hour : 4 Day:5 AffinityGroup Lookup Look up test case 1
  • the Ad-Track may provide access to information on
  • 16 centralized platform may be restricted based on the originator as well as application
  • the Ad-Track may thus is allow a variety of flexible application services to be built on a common database
  • the Ad-Track may generate, update, maintain, store and/or
  • the Ad-Track may store profile information on an issuer bank 902a (see profile
  • the Ad-Track may also store relationships between such
  • the Ad-Track may store information on a relationship of the
  • FIGURES 10A-F show block diagrams illustrating example aspects of data
  • the Ad-Track may store a variety of attributes of
  • the Ad-Track may store user profile attributes.
  • a user profile model may store user identifying information 1001, user
  • user financial attributes model may store user identifying information 1020, user
  • 14 payment card attributes data model may include field types such s, but not limited to:
  • 20 services attributes data model may include field types such as, but not limited to: user
  • 28 model may include field types such as, but not limited to: user identifying information
  • a user graph attributes data model may include field types such as, but not limited to: user identifying information 1080, user contact 1081, consumer application user alias status 1082, relationship 1083, and/or the like.
  • the Ad-Track may store each object (e.g., user, merchant, issuer, acquirer, IP address, household, etc.) as a node in graph database, and store data with respect to each node in a format such as the example format provided below:
  • TOKENENTITYKE Y 2b8494 flbdl cl Ie0acbd6d888c43f7c2 : TOKEN : 778 : 5

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Abstract

Les appareils, procédés et systèmes de plate-forme d'incitation ciblée et à notifications réduisant la largeur de bande bidirectionnelle (« Ad-Track ») transforment des données d'activité d'un client en transactions de paiement à partage des recettes publicitaires par l'intermédiaire de composants Ad-Track. Dans un mode de réalisation, un procédé d'augmentation de l'efficacité de transmission de données dans un réseau et de réduction de l'utilisation de la largeur de bande du réseau comprend les étapes consistant à : instancier un composant de suivi à distance sur un dispositif d'utilisateur ; recevoir un événement de sollicitation du client par rapport à un produit par l'intermédiaire du composant de suivi à distance ; déterminer un commerçant associé sur la base de l'événement de sollicitation, le commerçant vendant le produit ; et transmettre au client, par l'intermédiaire du composant de suivi à distance, un composant de publicité faisant la publicité du commerçant.
PCT/US2012/045875 2011-07-08 2012-07-07 Appareils, procédés et systèmes de plate-forme d'incitation ciblée et à notifications réduisant la largeur de bande bidirectionnelle Ceased WO2013009660A1 (fr)

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US201161505597P 2011-07-08 2011-07-08
US61/505,597 2011-07-08
US201261594063P 2012-02-02 2012-02-02
US61/594,063 2012-02-02
US13/520,481 US10223691B2 (en) 2011-02-22 2012-02-22 Universal electronic payment apparatuses, methods and systems
US201261620431P 2012-04-04 2012-04-04
US61/620,431 2012-04-04
US13/520,481 2012-07-03
US13/542,443 US10121129B2 (en) 2011-07-05 2012-07-05 Electronic wallet checkout platform apparatuses, methods and systems
US13/542,443 2012-07-05

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