OFFER PERSONALIZATION ENGINE FOR TARGETED MARKETING OF CONSUMER PACKAGED GOODS

Abstract

A method including receiving, in a dynamic creative rendering server, a request from a browser or mobile application, the request directed to an ad-creative display, is provided. The method also includes determining an identifier for the mobile device from a publisher website or application accessible to the mobile device, providing the identifier to an advertisement engine, and correlating the identifier with a frequent shopper identification in a lookup table in the advertisement engine, the frequent shopper identification associated with a retailer. The method also includes receiving a playlist including a structured content, processing the structured content and pushing the playlist including the structured content into the browser or mobile application. A system for performing the above method is also provided.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

The present disclosure is related to and claims priority under 35 U.S.C. § 119(e) of U.S. Provisional Patent Application No. 62/507,113, entitled “OFFER PERSONALIZATION ENGINE FOR TARGETED MARKETING OF CONSUMER PACKAGED GOODS,” by Zubin SINGH et-al, and to U.S. Provisional Patent Application No. 62/507,116, entitled “OFFER PERSONALIZATION ENGINE FOR TARGETED MARKETING OF BRANDED CONSUMER PACKAGED GOODS,” by Zubin SINGH et-al, both applications filed on May 16, 2017, and the contents of both applications are hereby incorporated by reference in their entirety, for all purposes.

BACKGROUND

Field

The present disclosure generally relates to the personalized delivery of retailer consumer packaged goods (CPGs)-based offer content through digital advertisements via mobile and desktop computer devices.

Description of the Related Art

CPG brands lose about one-third of their consumers every year due mainly to the inefficient advertising techniques typically oriented towards market segmentation through demographics. To improve efficiency, marketing tools available today involve a trade-off between sophistication, selectivity, scalability, and accessibility (e.g., mobile, online, or in store). However, sophisticated tools are too slow to be useful in the context of consumers of CPGs in a grocery store, and difficult to leverage at the scales desirable for such applications, such as the implementation of geofencing for in-store notifications.

SUMMARY

In one embodiment of the present disclosure, a computer-implemented method is described for receiving, in a dynamic creative rendering server, a request from a browser or mobile application in a mobile device, the request directed to an ad-creative display. The computer-implemented method also includes determining an identifier for the mobile device from a publisher website or application, the publisher website or application accessible to the mobile device and providing the identifier to an advertisement engine. The computer-implemented method also includes correlating the identifier with a frequent shopper identification in a lookup table in the advertisement engine, the frequent shopper identification associated with a retailer, receiving, after a logic query for the frequent shopper identification in the advertisement engine, a playlist including a structured content, and processing the structured content and pushing the playlist including the structured content into the browser or mobile application in the mobile device.

According to one embodiment, a system is described that includes one or more processors and a memory coupled to the one or more processors, the memory including instructions that, when executed by the one or more processors, cause the one or more processors to receive, in a dynamic creative rendering server, a request from a browser or mobile application in a mobile device, the request directed to an ad-creative display. The one or more processors also execute instructions to determine an identifier for the mobile device from a publisher website or application, the publisher website or application accessible to the mobile device and to provide the identifier to an advertisement engine. The one or more processors also execute instructions to correlate the identifier with a frequent shopper identification in a lookup table in the advertisement engine, the frequent shopper identification associated with a retailer, to receive, after a logic query for the frequent shopper identification in the advertisement engine, a playlist response including a structured content, and to process the structured content and push the playlist response including the structured content into the browser or mobile application in the mobile device.

According to one embodiment, a non-transitory, machine readable medium is described that includes instructions, which when executed by one or more processors, cause a computer to perform a method that includes integrating a mobile device attribute from a mobile device and a publisher attribute with a supply side platform to form a request for an advertisement bid. The method also includes providing, to a demand side platform, the request for an advertisement bid and receiving, from the demand side platform, a response to the request for the advertisement bid, wherein the response to the request for the advertisement bid includes an digital advertisement payload selected according to a digital identification of a consumer, and wherein the digital identification of the consumer is associated with the mobile device attribute. The method also includes selecting the response to the advertisement bid based on an auction for one or more bids from different providers, and delivering, by the supply side platform, the digital advertisement payload to a publisher website accessible to the mobile device, wherein the digital advertisement payload includes a script code to render a dynamic creative ad-unit in the mobile device based on the digital identification of the consumer.

In yet other embodiment, a system is described that includes a means for storing commands and a means for executing the commands causing the system to perform a method that includes integrating a mobile device attribute from a mobile device and a publisher attribute with a supply side platform to form a request for an advertisement bid. The method also includes providing, to a demand side platform, the request for an advertisement bid and receiving, from the demand side platform, a response to the request for the advertisement bid, wherein the response to the request for the advertisement bid includes an digital advertisement payload selected according to a digital identification of a consumer, and wherein the digital identification of the consumer is associated with the mobile device attribute. The method also includes selecting the response to the advertisement bid based on an auction for one or more bids from different providers, and delivering, by the supply side platform, the digital advertisement payload to a publisher website accessible to the mobile device, wherein the digital advertisement payload includes a script code to render a dynamic creative ad-unit in the mobile device based on the digital identification of the consumer.

In a further embodiment, a computer-implemented method is described for integrating a mobile device attribute from a mobile device and a publisher attribute with a supply side platform to form a request for an advertisement bid. The computer-implemented method includes providing, to a demand side platform, the request for an advertisement bid, and receiving, from the demand side platform, a response to the request for the advertisement bid, wherein the response to the request for the advertisement bid includes an digital advertisement payload selected according to a digital identification of a consumer, and wherein the digital identification of the consumer is associated with the mobile device attribute. The computer-implemented method also includes selecting the response to the advertisement bid based on an auction for one or more bids from different providers, and delivering, by the supply side platform, the digital advertisement payload to a publisher website accessible to the mobile device, wherein the digital advertisement payload includes a script code to render a dynamic creative ad-unit in the mobile device based on the digital identification of the consumer.

It is understood that other configurations of the subject technology will become readily apparent to those skilled in the art from the following detailed description, wherein various configurations of the subject technology are shown and described by way of illustration. As will be realized, the subject technology is capable of other and different configurations and its several details are capable of modification in various other respects, all without departing from the scope of the subject technology. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide further understanding and are incorporated in and constitute a part of this specification, illustrate disclosed embodiments and together with the description serve to explain the principles of the disclosed embodiments. In the drawings:

FIG. 1 illustrates an example architecture suitable for presenting personalized digital promotions to a consumer, according to some embodiments.

FIG. 2 is a block diagram illustrating an example server and client from the architecture of FIG. 1, according to certain aspects of the disclosure.

FIG. 3 illustrates a system including a mobile device and at least one network server, configured to provide a playlist of personalized MFDs to the user of the mobile device, according to some embodiments.

FIG. 4 illustrates a screenshot of a display provided by a publisher server in a supply side platform, including an advertisement payload provided by a dynamic creative rendering server in a demand side platform, according to some embodiments.

FIG. 5 illustrates a screenshot of a digital promotion when a consumer activates the advertisement payload, according to some embodiments.

FIG. 6 is a flow chart illustrating steps in a method for auctioning an advertisement space in a publisher website for an advertisement item payload from a server, according to some embodiments.

FIG. 7 is a flow chart illustrating steps in a method for preparing a personalized advertisement payload to a consumer, according to some embodiments.

FIG. 8 is a block diagram illustrating an example computer system with which the client and server of FIGS. 1 and 2 and the methods of FIGS. 6 and 7 can be implemented.

In the figures, elements and steps denoted by the same or similar reference numerals are associated with the same or similar elements and steps, unless indicated otherwise.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are set forth to provide a full understanding of the present disclosure. It will be apparent, however, to one ordinarily skilled in the art, that the embodiments of the present disclosure may be practiced without some of these specific details. In other instances, well-known structures and techniques have not been shown in detail so as not to obscure the disclosure.

General Overview

Marketing tools used for advertising universal product codes (UPCs) are largely ineffective, as they are typically based on demographic data for users, rather than their personalized purchasing history and habits. A major drawback for users in the CPG industry is the short time span between receiving an advertisement and executing a purchasing decision, in addition with the high mobility of the users in that same short time span (e.g., while moving through the aisles of a grocery store). This creates a bottleneck for information processing and accessibility in a networked database to provide a desirable advertisement at an appropriate time (e.g., advertising for household maintenance products when the user is in the household items aisle, or in a household item store).

The disclosed system addresses this problem specifically arising in the realm of computer technology by providing a solution also rooted in computer technology, namely, by a personalized digital media database for advertisement and promotions that may adapt across a wide range of modalities from mobile, to online, to the aisle of a grocery store.

The subject system provides several advantages, including providing an engine that enables to select a reduced set of advertisements and promotions from a weekly or other periodical circular, including hundreds of advertisements and promotions for multiple UPCs. In some embodiments, the circular is generated by a retail store that carries one or more of the multiple UPCs. The circular may be generated periodically (e.g., once a week) by a retail store in the interest of attracting customers and/or rewarding loyal customers having a frequent shopper identification (FSC ID). The retailer may decide to offer certain items for promotion. The system provides a reduced set of items to a user mobile device, based on an FSC ID and a purchasing history associated with the FSC ID.

The proposed solution further provides improvements to the functioning of the computer itself because it saves data storage space and reduces network usage (e.g., while transferring a reduced set of advertisements and promotions for display by the mobile device).

Embodiments as disclosed herein address the problem encountered in the field of real-time, personalized advertisement by selecting a limited amount of highly targeted data to transmit to a mobile device in real time. Furthermore, some embodiments may also address an issue that arises when multiple advertisement items are available, e.g., special offers and discounts, new products, and coupons, but a limited amount of time is available for a response. In such cases, some embodiments may include “my favorite deals” (MFDs) having, for example: ad offer content, bar-codes, in-store redeemable coupons, including geofencing for pushing location based notifications (e.g., within the store).

Although many examples provided herein describe a user's search inputs or purchasing history being identifiable, or download consumer history, each user may grant explicit permission for such user information to be shared or stored. In some embodiments, a retailer may establish an agreement with consumers registered with a frequent shopper identification to allow a third party dynamic rendering service in a demand side platform to provide targeted, personalized marketing offers to the consumer. In some embodiments, the consumer may opt out from receiving the marketing offers associated with one or more particular retailers. The explicit permission to participate and allow the targeted, personalized marketing offers may be granted using privacy controls integrated into the disclosed system. Each user may be provided notice that such user information will be shared with explicit consent, and each user may at any time terminate the information sharing, and may delete any stored user information. The stored user information may be encrypted to protect user security.

In some embodiments, methods as disclosed herein combine a predictive model to score a periodic deal offer content to a user (e.g., daily or weekly retailer circular) with basic category interest data for online offers. Some of the category interest data may include CPG categories such as “baby,” “beverage,” “food,” “general merchandise,” “health & beauty,” “over-the-counter,” “pet,” and the like. Some embodiments may include in-store shopping data for multiple users, available in a database through a network. In some embodiments, methods as disclosed herein include scoring circular advertisment item content (e.g., temporary price reductions), sourced by grocery retailers subscribed to a network service. Some embodiments include predicting circular advertisement item performance and modeling shopper behavior to predict likelihood of purchasing items in the retailer circular, for example by using machine learning algorithms, or appropriately trained neural networks.

In some embodiments, methods as disclosed herein accept online data and user activity for print-at-home offers. Such embodiments may be deployed to support a personalized user experience (e.g., for applying coupons). Further, some embodiments may accept load-to-card offers, where the card may be an FSC ID.

Example System Architecture

FIG. 1 illustrates an example architecture 100 for an advertisement engine suitable for practicing some implementations of the disclosure. Architecture 100 includes servers 130 and client devices 110 connected over a network 150. One of the many servers 130 is configured to host a memory, including instructions which, when executed by a processor, cause the server 130 to perform at least some of the steps in methods as disclosed herein. In some embodiments, architecture 100 is configured to present personalized digital promotions to a consumer, who may be the user of client device 110. The targeted advertisement payload may be retrieved from a purchase history of the user, which may be stored in a history log in a memory of the server.

Servers 130 may include any device having an appropriate processor, memory, and communications capability for hosting the history log, the advertisement database, and an advertisement engine. The advertisement engine may be accessible by various clients 110 over the network 150. In some embodiments, servers 130 may include a dynamic creative rendering server, a publisher, or supply side platform (SSP) server, and a demand side platform (DSP) server. Client devices 110 may include, for example, desktop computers, mobile computers, tablet computers (e.g., including e-book readers), mobile devices (e.g., a smartphone or PDA), or any other devices having appropriate processor, memory, and communications capabilities for accessing the image search engine and the history log on one or more of servers 130. Network 150 can include, for example, any one or more of a local area network (LAN), a wide area network (WAN), the Internet, and the like. Further, network 150 can include, but is not limited to, any one or more of the following network topologies, including a bus network, a star network, a ring network, a mesh network, a star-bus network, tree or hierarchical network, and the like.

FIG. 2 is a block diagram 200 illustrating an example server 130 and client device 110 in the architecture 100 of FIG. 1, according to certain aspects of the disclosure. Client device 110 and server 130 are communicatively coupled over network 150 via respective communications modules 218 and 238. Communications modules 218 and 238 are configured to interface with network 150 to send and receive information, such as data, requests, responses, and commands to other devices on the network. Communications modules 218 and 238 can be, for example, modems or Ethernet cards. Client device 110 may be coupled with an input device 214 and with an output device 216. Input device 214 may include a keyboard, a mouse, a pointer, or even a touch-screen display that a user (e.g., a consumer) may utilize to interact with client device 110. Likewise, output device 216 may include a display and a speaker with which the user may retrieve results from client device 110. Client device 110 may also include a processor 212, configured to execute instructions stored in a memory 220, and to cause client device 110 to perform at least some of the steps in methods consistent with the present disclosure. Memory 220 may further include an application 222 including specific instructions which, when executed by processor 212, cause an advertisement payload 225 from server 130 to be displayed for the consumer. Advertisement payload 225 may include multiple digital promotions or coupons presented to the consumer by server 130, and the consumer may store at least some of the digital promotions or coupons from advertisement payload 225 in memory 220.

Server 130 includes a memory 232, a processor 236, and communications module 238. Processor 236 is configured to execute instructions, such as instructions physically coded into processor 236, instructions received from software in memory 232, or a combination of both. Memory 232 includes an advertisement engine 242 for integrating images, videos, and other multimedia files stored in an advertisement database 252 into an advertisement payload. Advertisement engine 242 may push advertisements from advertisement database 252 to a user of client device 110 that is a consumer of a retailer store or chain of stores through an application 222 or a web browser installed in client device 110. Accordingly, application 222 may be installed by server 130 and perform scripts and other routines provided by server 130. In some embodiments, application 222 may be configured to display advertisement payload 225 provided by advertisement engine 242.

Advertisement engine 242 integrates advertisement payload 225 based on information retrieved from a frequent shopper identification database 254 and a history log database 256. History log database 256 includes the purchase history of multiple consumers listed in frequent shopper identification database 254. To achieve this, in some embodiments, an algorithm 244 stores commands which, when executed by processor 236, cause server 130 to integrate advertisement payload 225. Algorithm 244 may include a neural network (NN) trained over frequent shopper identification database 254 and history log database 256, to select advertisement payload 225 targeted to the specific preferences of a consumer when the consumer uses application 222 in client device 110 to access a network site hosted by server 130 (e.g., an SSP server). Accordingly, the SSP server hosting the network site accessed through application 222 may be different from a DSP server hosting advertisement engine 242.

In one or more implementations, advertisement database 252 integrates advertisement payloads including coupons and offers for multiple products on sale by a retailer having one or more stores. A frequent shopper identification database 254 may include a list of frequent consumers of the retailer. The consumers may have a frequent shopper identification associated with the retailer. In some embodiments, in addition to one or more “brick and mortar,” physical locations of stores for the retailer, the retailer may host an online shopping outlet hosted by a network server (e.g., server 130). Moreover, in some embodiments, a consumer, having a frequent shopper identification or not, may download an application (e.g., application 222) in client device 110 for the “online store” of the retailer. The retailer may create, update and maintain advertisement database 252, frequent shopper identification database 254, and history log database 256. In that regard, advertisement database 252, frequent shopper identification database 254, and history log database 256 may be hosted by the retailer, while the advertisement engine 242 may be hosted by a DSP server or a dynamic creative rendering server. Accordingly, the DSP server may have access to one or more advertisement databases 252, to one or more frequent shopper identification databases 254, and to one or more history log databases 256 through business agreements with one or more retailers.

In certain aspects, processor 236 in a server 130 hosted by a retailer is configured to determine data for history log database 256 by obtaining consumer purchasing data identifying the consumer via the frequent shopper identification used at multiple purchasing events in multiple locations, over a pre-selected span of time. In some embodiments, history log database 256 includes online purchasing history for the consumer through application 222 or a network browser.

FIG. 3 illustrates a system 300, including a mobile device and at least one network server, configured to provide a playlist of personalized MFDs to the user of the mobile device, according to some embodiments. The server may include a memory and a processor, wherein the memory may include, or may have access to, a database including a lookup table pairing a mobile device identifier (e.g., a mobile cookie ID or mobile advertising device identifier) with a retail-specific FSC ID, such as illustrated in TABLE I, below. In embodiments consistent with the present disclosure, the mobile cookie ID may be a mobile advertising device identifier, which in some embodiments may be different from a mobile device identifier used by a network service provider that services the operating system of the mobile device itself

TABLE 1
Mobile Cookie ID Database Retailer's FSC-ID
hsh192zur94      384759
Su928470184      495038
*Table 1 values are illustrative for examples purposes

System 300 may include an MFD engine 310. MFD engine 310 is a platform designed to score and rank the most relevant offers for an individual shopper from a pool of available retailer CPG content using historical consumer item level in-store purchase data from grocery retailers and online activity based on a predictive, computer-based method. The method may be optimized to drive incremental trips of the user to a store, and increased spending on each trip of the user to the store. In some embodiments, the method combines three components: an overall prediction of the offer performance (base rate), individual in-store shopping behavior and online interactions to predict a given shopper's likelihood to respond to each offer, and client specific business rules to adjust offer ranking based on secondary objectives. MFD engine 310 scores most or all of the offers for a shopper in near real-time. In some embodiments, MFD engine 310 is able to score the offers in under 500 milliseconds (ms), at the time of transaction, using the most up-to-date user data available. In some embodiments, the platform for MFD engine 310 is extensible to accommodate a variety of offers including digital “load-to-card” offers, print at home coupons, and circular advertisements for omni-channel delivery (e.g., in-store, online, email and mobile).

In some embodiments, MFD engine 310 is configured to select a few (e.g., ten, five, or maybe fewer) of the most relevant weekly promotional deals for a user who is an individual grocery shopper (which may include hundreds of UPCs), based on past in-store shopping behavior for the user, on UPC data, and on promotion details. MFD engine 310 may have access to several data sources, including the retailer's UPC Product Dictionary, Weekly Circular Ads, In-Store Point of Sale data, and Loyalty Card IDs.

System 300 may also include a DSP server 320 that has integrated attributes from a mobile display 301 and a mobile publisher website 305. Mobile publisher website 305 may include any mobile publisher application. DSP server 320 is configured to receive a request for an advertisement from the mobile publisher to which the mobile device has access.

System 300 may also include an SSP 330 for the mobile publisher website or mobile publisher application. In some embodiments, SSP 330 sends a bid request to DSP 320. Accordingly, SSP 330 may reply with a bid response including a digital MFD ad unit.

SSP 330 may conduct an auction for bids received from one or more vendors, and select the bid response from DSP 320. Further, SSP 330 may deliver the ad-payload to publisher website or mobile publisher application 305. In some embodiments, the payload may include a script (e.g., a javascript, “.js” code) to render the dynamic creative ad-unit.

A browser or mobile application in mobile device 301 may call a dynamic creative rendering server 340 to fetch an ad-creative element 325 (e.g., advertisement payload 225) including one or more digital promotions and/or coupons. Dynamic creative rendering server 340 may be configured to identify the incoming HTTP application programming interface (API) calling from publisher's website or mobile application 305 or an application in mobile device 301, containing an identifier for mobile device 301. Dynamic creative rendering server 340 may then execute commands in an API to provide the identifier of mobile device 301 to MFD engine 310.

MFD engine 310 may be configured to execute logic commands that use the identifier of mobile device 301 and cross-walk an ID mapping table (e.g., TABLE I, above) to look up the corresponding retailer's FSC ID (frequent shopper identification ID). MFD engine 310 may also be configured to execute internal logic to query the retailer's FSC ID. MFD engine 310 may then return a “.json” or an “.xml” playlist of structured MFD content to dynamic creative rendering server 340.

In some embodiments, the logic commands used in MFD engine 310 include a combination of a content-based filtering recommendator system (e.g., that may be used to recommend music choices for a user), a Recency-Frequency-Monentary (RFM) Model, which may also be used for direct marketing campaigns, and predictive statistical modeling. In embodiments consistent with the present disclosure, MFD engine 310 solves at least two problems encountered in the realm of computer techniques for personalized and mobile marketing strategies. First, a scalable way to personalization CPG and grocery offers when the pool of content is relatively large (more than 300 offers in a retailer circular, for example) for each individual shopper. Traditionally, segmentation (e.g., user demographics, and the like) and look-a-like models have been used to group shoppers and then select the most appropriate offers. A personalization algorithm as used in the logic commands executed by MFD engine 310 is an effective way to determine the most relevant offers based on the unique behavior of the user. Second, the logic commands executed by MFD engine 310 execute rapidly, calculating the score and delivering the recommendations in under 500 ms, according to some embodiments.

Dynamic creative rendering server 340 pushes the dynamic “.json” or “.xml” playlist content provided by MFD engine 310 onto mobile device 101. Accordingly, the “.json” or “.xml” playlist may include a list of limited advertisement items (e.g., ads, coupons, and the like) that may be rendered within a Dynamic Creative ad-unit invoked and displayed on a mobile device 301 by SSP 330. Thus, advertisement items will be rendered and displayed in mobile device 301 for the user quickly and efficiently (e.g., as the user walks through the aisles in a grocery store, or at the cashier, to apply coupons at the time of payment). In some embodiments, including geofencing for in-store notifications, dynamic creative rendering server 340 pushes the dynamic “.json” or “.xml” playlist content when it is determined that the mobile device is within the confines of a retail store subscribed to system 300, wherein CPGs identified with UPCs handled by MFD engine 310 are sold.

In one aspect, a method may be an operation, an instruction, or a function and vice versa. In one aspect, a claim may be amended to include some or all of the words (e.g., instructions, operations, functions, or components) recited in other one or more claims, one or more words, one or more sentences, one or more phrases, one or more paragraphs, and/or one or more claims.

FIG. 4 illustrates a screenshot of a display 400 provided by a publisher server in a supply side platform, including an advertisement payload 425 provided by a dynamic creative rendering server in a demand side platform, according to some embodiments. Display 422 may include a webpage accessed by a browser or a mobile application 422 installed in client device 110.

Accordingly, the publisher server may auction a portion of display 400 for advertisement space to a DSP server that includes advertisement engine 242. After presenting a winning bid for the advertising space with the publisher server, the DSP server (e.g., DSP 320) may then provide an advertisement payload 425 branded for and including offers for the respective retailer 432. Advertisement payload 425 may include multiple digital promotions 435-1, 435-2, 435-3, 435-4, and 435-5 (hereinafter, collectively referred to as “loaded digital promotions 435”) selected from advertisement database 252. In some embodiments, advertisement payload 425 may include scrolling elements 427 so that the consumer may browse through digital promotions 435.

In some embodiments, retailer 432 in display 400 is a plugin for the consumer handling client device 110 to access an application or a website hosted by retailer 432. By clicking on the icon for retailer 432, the consumer may be directed to the retailer website or application, wherein the consumer may in fact browse for, and select, more digital promotions from retailer 432. In some embodiments, upon clicking a “save offer” button 437 in one of loaded digital promotions 435, the consumer may be prompted to install the retailer application (when the retailer application is not already installed in client device 110), or to launch the retailer application (when the retailer application is already installed in client device 110). Moreover, upon activating save offer button 437, in some embodiments, the DSP server may prompt the consumer to save one or more of loaded digital promotions 435 in the memory of the client device (e.g., memory 220). For example, the DSP server may prompt the consumer to save advertisement payload 425 in memory 220 (within client device 110), in a memory of the DSP server, or in a memory of a retailer server (e.g., memory 232, frequent shopper identification database 254, or history log database 256).

FIG. 5 illustrates a screenshot of a digital promotion 500A when the consumer activates save offer button 437 in one of loaded digital promotions 435 from advertisement payload 425, according to some embodiments. In some embodiments, digital promotion 500A may include a “load to memory” button 537 so that the consumer may load digital promotion 500A into a memory of the client device (e.g., memory 220). When load to memory button 537 is activated, some embodiments display a digital promotion preview 500B, including an expiration date 538. Digital promotion preview 500B may include “Load” and “Cancel” buttons 527a and 527c, respectively, to load coupon 500A to the memory, or cancel the operation. The consumer may bring all the promotions uploaded to memory 220 using the FSC-ID at the retailer store (“brick and mortar,” or online), or at any other point in time or place.

FIG. 6 illustrates steps in a method 600 for auctioning an advertisement space in a publisher website (e.g., publisher SSP 330) for an advertisement item payload from a DSP server (e.g., advertisement payloads 225, 325 and 425, DSP 320), according to some embodiments. Method 600 may be performed at least partially by any one of the plurality of servers illustrated in FIG. 3. For example, at least some of the steps in method 600 may be performed by one component in a system, including a mobile device running code for a browser and an application to access the publisher website, and an MFD engine that processes logic to select advertisement playlist for a dynamic creative rendering server to push the advertisement payload to the mobile device, the system also including a publisher SSP that requests advertisement bids from, and is registered with, a DSP server (e.g., system 300, mobile device 301, publisher website 305, MFD engine 310, DSP 320, publisher SSP 330, and dynamic creative rendering server 340). Accordingly, at least some of the steps in method 600 may be performed by a processor executing commands stored in a memory of the server, or accessible by the server. Further, in some embodiments, at least some of the steps in method 600 may be performed overlapping in time, almost simultaneously, or in a different order from the order illustrated in method 600. Moreover, a method consistent with some embodiments disclosed herein may include at least one, but not all, of the steps in method 600.

Step 602 includes integrating a mobile device attribute and a publisher attribute with the SSP to form a request for an advertisement bid. In some embodiments, the SSP is a multimedia content provider and step 602 includes selecting a portion of a window opened by the multimedia content provider in a display of the mobile device to display the digital advertisement payload.

Step 604 includes providing, from the SSP to the DSP, the request for an advertisement bid.

Step 606 includes receiving, from the DSP, a response to the request for the advertisement bid, wherein the response to the request for the advertisement bid includes a digital advertisement payload selected according to a digital identification of a consumer, and the digital identification of the consumer is associated with the mobile device attribute.

Step 608 includes selecting the response to the advertisement bid based on an auction for one or more bids from different providers.

Step 610 includes delivering, by the SSP, the digital advertisement payload to a publisher website or a mobile application accessible to the mobile device, wherein the digital advertisement payload includes a script code (e.g., a javascript code) to render a dynamic creative ad-unit in the mobile device, based on the digital identification of the consumer. The dynamic creative ad-unit may include a carousel with a few images displaying the targeted offers from the retailer circular selected for the user by the MFD engine. In some embodiments, step 610 includes delivering a personalized advertisement payload based on a previous purchasing history of the mobile device with a retailer that owns the digital advertisement payload. In some embodiments, the supply side platform includes a video publisher, and step 610 includes overlapping the digital advertisement payload, at least partially, in space and in time with a streaming video provided to the mobile device attribute.

FIG. 7 illustrates steps in a method 700 for rendering and displaying ads in a mobile device from an MFD engine, according to some embodiments. Method 700 may be performed at least partially by any one of the plurality of servers illustrated in FIG. 3. For example, at least some of the steps in method 700 may be performed by one component in a system, including a mobile device running code for a browser and an application to access a publisher website, and an MFD engine that processes logic to select advertisement playlist for a dynamic creative rendering server to push to the mobile device, the system also including a publisher SSP that requests advertisement bids from and is registered with a DSP (e.g., system 300, mobile device 301, publisher website 305, MFD engine 310, DSP 320, publisher SSP 330, and dynamic creative rendering server 340). Accordingly, at least some of the steps in method 300 may be performed by a processor executing commands stored in a memory of the server, or accessible by the server. Further, in some embodiments, at least some of the steps in method 700 may be performed overlapping in time, almost simultaneously, or in a different order than the order illustrated in method 700. Moreover, a method consistent with some embodiments disclosed herein may include at least one, but not all, of the steps in method 700.

Step 702 includes receiving, in a dynamic creative rendering server, a request from a mobile device browser or mobile application on a mobile device, the request directed to an ad-creative display.

Step 704 includes determining a mobile device identifier from a publisher website or application, the publisher website or application accessible to the mobile device.

Step 706 includes providing the mobile device identifier to the advertisement engine (e.g., the MFD engine). In some embodiments, step 706 includes identifying a frequent shopper identification identifier for a consumer based on the mobile device identifier, and providing the frequent shopper identification identifier to the advertisement engine.

Step 708 includes correlating the mobile device identifier with a corresponding frequent shopper identification (e.g., a FSC ID card) associated with a retailer.

Step 710 includes receiving, after a logic query for the frequent shopper identification in the advertisement engine, a playlist including structured advertisement content. In some embodiments, step 710 includes retrieving a purchasing history of a consumer from a history log database associated with the retailer, and selecting the structured content based on an advertisement database associated with the retailer and the purchasing history of the consumer.

Step 712 includes processing the structured advertisement content and pushing the playlist including the structured advertisement content into the mobile device browser or mobile application on the mobile device. In some embodiments, step 712 may include determining that the mobile device is within the confines of a retail store subscribed to system 300, wherein CPGs identified with UPCs handled by the MFD engine are sold. Further, in some embodiments, step 712 may include displaying the playlist for the user. For example, in some embodiments, the playlist includes a carousel of advertisements and offers for a limited number of CPGs (e.g., ten, five, or even less), which may be the few CPGs in the circular prepared by the retail store that the user is most likely to purchase or to at least have an immediate interest, according to the MFD engine. The carousel may be configured to rotate images with an incremental delay between images. When the user clicks on any image, the mobile device may store the UPC for the item that was selected and an API in the mobile device (e.g., an API handled by SSP 330, such as a mobile wallet) may push a reminder for the user that there is an offer at the retail store for the CPG identified by the UPC.

In some embodiments, step 712 includes providing a bid for the ad-creative display to a supply side platform hosting the publisher website. In some embodiments, step 712 includes determining a relevance value for a digital promotion selected from an advertisement database based on a purchase history of a consumer retrieved from a history log database based on the identifier, and sorting multiple digital promotions in the playlist, according to the relevance value provided by the advertisement engine. In some embodiments, step 712 includes providing a same bid with different advertisement playlists from a same retailer to multiple consumers based on a purchasing history of the consumers retrieved from history log database based on a different frequent shopper identification identifier for each of the consumers.

In some embodiments, step 712 includes providing, in the playlist, a link for a user of the mobile device to access a network site hosted by the retailer. In some embodiments, step 712 includes providing, in the playlist, a plugin to install an application for the retailer in the mobile device. In some embodiments, step 712 includes providing, in the playlist, a plugin for a user of the mobile device to execute a wallet application installed in the mobile device. In some embodiments, step 712 includes providing, in the playlist, a plugin for a user of the mobile device to store the playlist in a memory of the mobile device.

Hardware Overview

FIG. 8 is a block diagram illustrating an exemplary computer system 800 with which the client device 110 and server 130 of FIGS. 1 and 2, and the methods of FIGS. 6 and 7 can be implemented. In certain aspects, the computer system 800 may be implemented using hardware or a combination of software and hardware, either in a dedicated server, or integrated into another entity, or distributed across multiple entities.

Computer system 800 (e.g., client device 110 and server 130) includes a bus 808 or other communication mechanism for communicating information, and a processor 802 (e.g., processors 212 and 236) coupled with bus 808 for processing information. By way of example, the computer system 800 may be implemented with one or more processors 802. Processor 802 may be a general-purpose microprocessor, a microcontroller, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a state machine, gated logic, discrete hardware components, or any other suitable entity that can perform calculations or other manipulations of information.

Computer system 800 can include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them stored in an included memory 804 (e.g., memories 220 and 232), such as a Random Access Memory (RAM), a flash memory, a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable PROM (EPROM), registers, a hard disk, a removable disk, a CD-ROM, a DVD, or any other suitable storage device, coupled to bus 808 for storing information and instructions to be executed by processor 802. The processor 802 and the memory 804 can be supplemented by, or incorporated in, special purpose logic circuitry.

The instructions may be stored in the memory 804 and implemented in one or more computer program products, e.g., one or more modules of computer program instructions encoded on a computer readable medium for execution by, or to control the operation of, the computer system 800, and according to any method well known to those of skill in the art, including, but not limited to, computer languages such as data-oriented languages (e.g., SQL, dBase), system languages (e.g., C, Objective-C, C++, Assembly), architectural languages (e.g., Java, .NET), and application languages (e.g., PHP, Ruby, Perl, Python). Instructions may also be implemented in computer languages such as array languages, aspect-oriented languages, assembly languages, authoring languages, command line interface languages, compiled languages, concurrent languages, curly-bracket languages, dataflow languages, data-structured languages, declarative languages, esoteric languages, extension languages, fourth-generation languages, functional languages, interactive mode languages, interpreted languages, iterative languages, list-based languages, little languages, logic-based languages, machine languages, macro languages, metaprogramming languages, multiparadigm languages, numerical analysis, non-English-based languages, object-oriented class-based languages, object-oriented prototype-based languages, off-side rule languages, procedural languages, reflective languages, rule-based languages, scripting languages, stack-based languages, synchronous languages, syntax handling languages, visual languages, wirth languages, and xml-based languages. Memory 804 may also be used for storing temporary variable or other intermediate information during execution of instructions to be executed by processor 802.

A computer program as discussed herein does not necessarily correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, subprograms, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network. The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output.

Computer system 800 further includes a data storage device 806 such as a magnetic disk or optical disk, coupled to bus 808 for storing information and instructions. Computer system 800 may be coupled via input/output module 810 to various devices. Input/output module 810 can be any input/output module. Exemplary input/output modules 810 include data ports such as USB ports. The input/output module 810 is configured to connect to a communications module 812. Exemplary communications modules 812 (e.g., communications modules 218 and 238) include networking interface cards, such as Ethernet cards and modems. In certain aspects, input/output module 810 is configured to connect to a plurality of devices, such as an input device 814 (e.g., input device 214) and/or an output device 816 (e.g., output device 216). Exemplary input devices 814 include a keyboard and a pointing device, e.g., a mouse or a trackball, by which a user can provide input to the computer system 800. Other kinds of input devices 814 can be used to provide for interaction with a user as well, such as a tactile input device, visual input device, audio input device, or brain-computer interface device. For example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, tactile, or brain wave input. Exemplary output devices 816 include display devices, such as an LCD (liquid crystal display) monitor, for displaying information to the user.

According to one aspect of the present disclosure, the client device 110 and server 130 can be implemented using a computer system 800 in response to processor 802 executing one or more sequences of one or more instructions contained in memory 804. Such instructions may be read into memory 804 from another machine-readable medium, such as data storage device 806. Execution of the sequences of instructions contained in main memory 804 causes processor 802 to perform the process steps described herein. One or more processors in a multi-processing arrangement may also be employed to execute the sequences of instructions contained in memory 804. In alternative aspects, hard-wired circuitry may be used in place of or in combination with software instructions to implement various aspects of the present disclosure. Thus, aspects of the present disclosure are not limited to any specific combination of hardware circuitry and software.

Various aspects of the subject matter described in this specification can be implemented in a computing system that includes a back end component, e.g., a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification, or any combination of one or more such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. The communication network (e.g., network 150) can include, for example, any one or more of a LAN, a WAN, the Internet, and the like. Further, the communication network can include, but is not limited to, for example, any one or more of the following network topologies, including a bus network, a star network, a ring network, a mesh network, a star-bus network, tree or hierarchical network, or the like. The communications modules can be, for example, modems or Ethernet cards.

Computer system 800 can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. Computer system 800 can be, for example, and without limitation, a desktop computer, laptop computer, or tablet computer. Computer system 800 can also be embedded in another device, for example, and without limitation, a mobile telephone, a PDA, a mobile audio player, a Global Positioning System (GPS) receiver, a video game console, and/or a television set top box.

The term “machine-readable storage medium” or “computer readable medium” as used herein refers to any medium or media that participates in providing instructions to processor 802 for execution. Such a medium may take many forms, including, but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical or magnetic disks, such as data storage device 806. Volatile media include dynamic memory, such as memory 804. Transmission media include coaxial cables, copper wire, and fiber optics, including the wires forming bus 808. Common forms of machine-readable media include, for example, floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH EPROM, any other memory chip or cartridge, or any other medium from which a computer can read. The machine-readable storage medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter affecting a machine-readable propagated signal, or a combination of one or more of them.

To illustrate the interchangeability of hardware and software, items such as the various illustrative blocks, modules, components, methods, operations, instructions, and algorithms have been described generally in terms of their functionality. Whether such functionality is implemented as hardware, software, or a combination of hardware and software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application.

As used herein, the phrase “at least one of” preceding a series of items, with the terms “and” or “or” to separate any of the items, modifies the list as a whole, rather than each member of the list (e.g., each item). The phrase “at least one of” does not require selection of at least one item; rather, the phrase allows a meaning that includes at least one of any one of the items, and/or at least one of any combination of the items, and/or at least one of each of the items. By way of example, the phrases “at least one of A, B, and C” or “at least one of A, B, or C” each refer to only A, only B, or only C; any combination of A, B, and C; and/or at least one of each of A, B, and C.

The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. Phrases such as an aspect, the aspect, another aspect, some aspects, one or more aspects, an implementation, the implementation, another implementation, some implementations, one or more implementations, an embodiment, the embodiment, another embodiment, some embodiments, one or more embodiments, a configuration, the configuration, another configuration, some configurations, one or more configurations, the subject technology, the disclosure, the present disclosure, other variations thereof and alike are for convenience and do not imply that a disclosure relating to such phrase(s) is essential to the subject technology or that such disclosure applies to all configurations of the subject technology. A disclosure relating to such phrase(s) may apply to all configurations, or one or more configurations. A disclosure relating to such phrase(s) may provide one or more examples. A phrase such as an aspect or some aspects may refer to one or more aspects and vice versa, and this applies similarly to other foregoing phrases.

A reference to an element in the singular is not intended to mean “one and only one” unless specifically stated, but rather “one or more.” Pronouns in the masculine (e.g., his) include the feminine and neuter gender (e.g., her and its) and vice versa. The term “some” refers to one or more. Underlined and/or italicized headings and subheadings are used for convenience only, do not limit the subject technology, and are not referred to in connection with the interpretation of the description of the subject technology. Relational terms such as first and second and the like may be used to distinguish one entity or action from another without necessarily requiring or implying any actual such relationship or order between such entities or actions. All structural and functional equivalents to the elements of the various configurations described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and intended to be encompassed by the subject technology. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the above description. No claim element is to be construed under the provisions of 35 U.S.C. § 112, sixth paragraph, unless the element is expressly recited using the phrase “means for” or, in the case of a method claim, the element is recited using the phrase “step for.”

While this specification contains many specifics, these should not be construed as limitations on the scope of what may be described, but rather as descriptions of particular implementations of the subject matter. Certain features that are described in this specification in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially described as such, one or more features from a described combination can in some cases be excised from the combination, and the described combination may be directed to a subcombination or variation of a subcombination.

The subject matter of this specification has been described in terms of particular aspects, but other aspects can be implemented and are within the scope of the following claims. For example, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. The actions recited in the claims can be performed in a different order and still achieve desirable results. As one example, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the aspects described above should not be understood as requiring such separation in all aspects, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

The title, background, brief description of the drawings, abstract, and drawings are hereby incorporated into the disclosure and are provided as illustrative examples of the disclosure, not as restrictive descriptions. It is submitted with the understanding that they will not be used to limit the scope or meaning of the claims. In addition, in the detailed description, it can be seen that the description provides illustrative examples and the various features are grouped together in various implementations for the purpose of streamlining the disclosure. The method of disclosure is not to be interpreted as reflecting an intention that the described subject matter requires more features than are expressly recited in each claim. Rather, as the claims reflect, inventive subject matter lies in less than all features of a single disclosed configuration or operation. The claims are hereby incorporated into the detailed description, with each claim standing on its own as a separately described subject matter.

The claims are not intended to be limited to the aspects described herein, but are to be accorded the full scope consistent with the language claims and to encompass all legal equivalents. Notwithstanding, none of the claims are intended to embrace subject matter that fails to satisfy the requirements of the applicable patent law, nor should they be interpreted in such a way.

Claims

1. A computer-implemented method, comprising:

receiving, in a dynamic creative rendering server, a request from a browser or mobile application on a mobile device, the request directed to an ad-creative display;

determining an identifier for the mobile device from a publisher website or application, the publisher website or application accessible to the mobile device;

providing the identifier to an advertisement engine;

correlating the identifier with a frequent shopper identification in a lookup table in the advertisement engine, the frequent shopper identification associated with a retailer;

receiving, after a logic query for the frequent shopper identification in the advertisement engine, a playlist including a structured content; and

processing the structured content and pushing the playlist including the structured content into the browser or mobile application on the mobile device.

2. The computer-implemented method of claim 1, further comprising:

retrieving a purchasing history of a consumer from a history log database associated with the retailer, and

selecting the structured content based on an advertisement database associated with the retailer and the purchasing history of the consumer.

3. The computer-implemented method of claim 1, wherein processing the structured content and pushing the playlist comprises providing a bid for the ad-creative display to a supply side platform hosting the publisher website.

4. The computer-implemented method of claim 1, wherein processing the structured content comprises:

determining a relevance value for a digital promotion selected from an advertisement database based on a purchase history of a consumer retrieved from a history log database based on the identifier, and

sorting multiple digital promotions in the playlist according to the relevance value provided by the advertisement engine.

5. The computer-implemented method of claim 1, wherein processing the structured content and pushing the playlist comprises providing a same bid with different advertisement playlists from a same retailer to multiple consumers based on a purchasing history of the consumers retrieved from history log database based on a different frequent shopper identification identifier for each of the consumers.

6. The computer-implemented method of claim 1, further comprising providing, in the playlist, a link for a user of the mobile device to access a network site hosted by the retailer.

7. The computer-implemented method of claim 1, further comprising providing, in the playlist, a plugin to install an application for the retailer in the mobile device.

8. The computer-implemented method of claim 1, further comprising providing, in the playlist, a plugin for a user of the mobile device to execute a wallet application installed in the mobile device.

9. The computer-implemented method of claim 1, further comprising providing, in the playlist, a plugin for a user of the mobile device to store the playlist in a memory of the mobile device.

10. The computer-implemented method of claim 1, wherein a content in the structured content of the playlist is selected by the retailer and updated by the retailer on a pre-determined schedule.

11. A system, comprising:

one or more processors; and

a memory coupled to the one or more processors, the memory including instructions that, when executed by the one or more processors, cause the one or more processors to: receive, in a dynamic creative rendering server, a request from a browser or mobile application on a mobile device, the request directed to an ad-creative display; determine an identifier for the mobile device from a publisher website or application, the publisher website or application accessible to the mobile device; provide the identifier to an advertisement engine; correlate the identifier with a frequent shopper identification in a lookup table in the advertisement engine, the frequent shopper identification associated with a retailer; receive, after a logic query for the frequent shopper identification in the advertisement engine, a playlist response including a structured content; and process the structured content and push the playlist response including the structured content into the browser or mobile application on the mobile device.

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

retrieve a purchasing history of a consumer from a history log database associated with the retailer, and

select the structured content based on an advertisement database associated with the retailer and the purchasing history of the consumer.

13. The system of claim 11, wherein to process the structured content and push the playlist response the one or more processors further execute instructions to provide a bid for the ad-creative display to a supply side platform hosting the publisher website.

14. The system of claim 11, wherein to process the structured content the one or more processors further execute instructions to determine a relevance value for a digital promotion selected from an advertisement database based on a purchase history of a consumer retrieved from a history log database based on the identifier, and to sort multiple digital promotions in the playlist response according to the relevance value provided by the advertisement engine.

15. The system of claim 11, wherein the one or more processors further execute instructions to provide, in the playlist response, a link for a user of the mobile device to access a network site hosted by the retailer.

16. The system of claim 11, wherein the one or more processors further execute instructions to provide, in the playlist response, a plugin to install an application for the retailer in the mobile device.

17. A computer-implemented method, comprising:

integrating a mobile device attribute from a mobile device and a publisher attribute with a supply side platform to form a request for an advertisement bid;

providing, to a demand side platform, the request for an advertisement bid;

receiving, from the demand side platform, a response to the request for the advertisement bid, wherein the response to the request for the advertisement bid includes an digital advertisement payload selected according to a digital identification of a consumer, and wherein the digital identification of the consumer is associated with the mobile device attribute;

selecting the response to the advertisement bid based on an auction for one or more bids from different providers; and

delivering, by the supply side platform, the digital advertisement payload to a publisher website accessible to the mobile device, wherein the digital advertisement payload includes a script code to render a dynamic creative ad-unit in the mobile device based on the digital identification of the consumer.

18. The computer-implemented method of claim 17, wherein the supply side platform is a multimedia content provider and integrating a mobile device attribute from a mobile device and a publisher attribute comprises selecting a portion of a window opened by the multimedia content provider in a display of the mobile device to display the digital advertisement payload.

19. The computer-implemented method of claim 17, wherein delivering the digital advertisement payload to a publisher website accessible to the mobile device comprises delivering a personalized advertisement payload based on a previous purchasing history of the mobile device with a retailer that owns the digital advertisement payload.

20. The computer-implemented method of claim 17, wherein the supply side platform includes a video publisher, and delivering the digital advertisement payload comprises overlapping the digital advertisement payload, at least partially, in space and in time with a streaming video provided to the mobile device attribute.