US20230153858A1 - Systems and Methods for Statistical Dynamic Geofencing - Google Patents

Abstract

Systems and methods for statistical dynamic geofencing are discussed. For example, a method for statistical dynamic geofencing can include operations such as receiving a location-based campaign request, analyzing demographic data, determining a geofence parameter, generating a geofence, and distributing location-aware advertisements. The location-based campaign request can include a list of points of interest (POIs) and a target demographic parameter. The demographic data can include data from geographic areas surrounding at least a portion of the POIs as well as data related to the target demographic parameter. The geofence can be generated based at least in part on the geofence parameter, where the geofence parameter directly affects either the size or shape of the geofence. The location-aware advertisements are distributed to a plurality of mobile devices determined to be within the geofence.

Description

CLAIM OF PRIORITY
• This application is a continuation of and claims priority to U.S. patent application Ser. No. 16/506,488, filed Jul. 9, 2019, which in turn is a continuation of and claims priority to U.S. patent application Ser. No. 13/707,316, filed Dec. 6, 2012, which is now U.S. Pat. No. 10,380,636, issued Aug. 13, 2019, the entire disclosure of which is hereby incorporated by reference herein in its entirety.
TECHNICAL FIELD
• This application relates generally to data processing within a network-based system operating over a distributed network or data processing on a mobile device, and more specifically to systems and methods for implementing statistical dynamic geofencing.
BACKGROUND
• The ever increasing use of smart phones, such as the iPhone® (from Apple, Inc. of Cupertino, Calif.), with data connections and location determination capabilities is slowly changing the way people interact, shop for products and services, and even manage accounts. Smart phones can provide users with nearly instant information regarding a wide range of information, such as product availability, friend locations, or pricing. For example, applications such as RedLaser™ (from eBay, Inc. of San Jose, Calif.) allow a smart phone user to scan a bar code and instantly check prices across online and local retail outlets. Smart phones also commonly include mechanisms, such as global positioning system (GPS) receivers, that allow the devices to constantly update location information. These technology changes are also driving changes in the way merchants and brand advertisers target and deliver advertising, particularly mobile advertising.
BRIEF DESCRIPTION OF THE DRAWINGS
• Some embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings in which:
• FIG.1 is a block diagram depicting a system for using statistical dynamic geofences to assist in targeted publication distribution, according to an example embodiment.
• FIG.2 is a block diagram illustrating an environment for operating a mobile device, according to an example embodiment.
• FIG.3 is a block diagram illustrating a mobile device, according to an example embodiment.
• FIG.4 is a block diagram illustrating a network-based system for using statistical dynamic geofences to assist in targeted publication distribution, according to an example embodiment.
• FIG.5 is a block diagram illustrating geofencing modules, according to an example embodiment.
• FIG.6 is a diagram illustrating geofence updating via statistical analysis, according to an example embodiment.
• FIG.7 is a flowchart illustrating a method of generating and using statistical dynamic geofences to assist in targeted publication distribution, according to an example embodiment.
• FIG.8 is a flowchart illustrating a method of updating statistical dynamic geofences to refine targeted publication distribution, according to an example embodiment.
• FIG.9 is a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions for causing the machine to perform any one or more of the methodologies discussed herein may be executed.
DEFINITIONS
• Location—For the purposes of this specification and the associated claims, the term “location” is used to refer to a geographic location, such as a longitude/latitude combination or a street address. The term location is also used within this specification in reference to a physical location associated with a merchant, an event, or other similar physical destination.
• Point of Interest (POI)—For the purposes of this specification and the associated claims, the term POI is used in a manner similar to location, and refers to or identifies a geographic (physical) location. For example, a POI may be a retail store, such as Starbucks, and may identify that retail store by name, address, GPS coordinates, or any other known method of identifying a unique physical location.
• Real-time—For the purposes of this specification and the associated claims, the term “real-time” is used to refer to calculations or operations performed on the fly as events occur or input is received by the operable system. However, the use of the term “real-time” is not intended to preclude operations that cause some latency between input and response, so long as the latency is an unintended consequence induced by the performance characteristics of the machine.
• Context—For the purposes of this specification and the associated claims, the term “context” is used to refer to environmental inputs, such as location, time, and weather conditions, among others. The context generally refers to conditions describing an individual's (e.g., user's) environment and/or activities. For example, context information can include a user's location, direction of movement, current activity (e.g., working, driving, playing golf, shopping, etc.), current weather conditions, time of day, and time of year (e.g., season), among other things. In certain examples, context information about a user can also include past events, purchase history, or other historical data about the user.
• Geofence—For the purposes of this specification and the associated claims, the term “geofence” is used to refer to various regions or boundaries of interest that include a geographic area within a distance or travel time to a point of interest. However, a geofence need not be limited to any geometric shape or an arbitrary boundary drawn on a map. A geofence can be used to determine a geographical area of interest for calculation of demographics, advertising, or similar purposes. Geofences can be used in conjunction with the advertisement generation and delivery concepts discussed herein. For example, a geofence can be used to assist in determining whether a user (or mobile device associated with the user) is within a geographic area of interest to a particular advertiser (e.g., a local merchant) or capable of traveling to the particular advertiser in a specified period of time. If the user is within a geofence established by the merchant, the systems discussed herein can use that information to generate a dynamic advertisement from the advertiser and deliver the offer to the user (e.g., via a mobile device associated with the user).
• Additional detail regarding providing and receiving location-based services, including geo-location and geofence concepts, can be found in U.S. Pat. No. 7,848,765, titled “Location-Based Services,” granted to Phillips et al., which is hereby incorporated by reference.
DETAILED DESCRIPTION
• Example systems and methods are described for using statistical dynamic geofencing for targeting publication delivery to mobile devices, among other things. Also described are systems and methods for generating, updating, and utilizing statistical dynamic geofences. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of example embodiments. It will be evident, however, to one skilled in the art, that the present invention may be practiced without these specific details. It will also be evident that statistical dynamic geofencing is not limited to the examples provided and may include other scenarios not specifically discussed.
• Geofences can be used within a location-aware publication system to target publications for distribution within limited geographical areas. Geofences can be defined in terms of GPS coordinates (e.g., latitude and longitude) combined with a radius measured in meters or feet, for example. Alternatively, geofences can also be defined according to a series of GPS coordinates defining a bounding box. In yet other examples, a geofence can be any geometric shape defined by a mathematical formula and anchored by a GPS coordinate. Other methods of defining, maintaining, and using geofences can be used without limitation with the systems and methods discussed herein.
• One challenge identified by the inventors in effective use of geofences for targeting publication distribution can include accurately predicting whether the geofence is likely to include target consumers who are likely to respond to the publication. A solution to this challenge can include the use of statistical analysis of demographic data, such as census data, in geographic areas of interest to determine optimal geofence size, shape, and even placement. Targeting publications, such as advertisements, for distribution within limited geographical areas can allow merchants and other advertisers to selectively target publications based on statistical analysis of data, such as demographic data.
• With the increased popularity of mobile devices, such as the iPhone®, with location-aware capabilities, the usefulness of location-aware publication systems has increased. Location-aware publication systems can receive location data on mobile devices directly from individual mobile devices or from a carrier, such as AT&T or Verizon. In some examples, the location data may also include, or be able to be correlated with, demographic data associated with the users of the mobile devices. In such examples, a location-aware publication system can analyze historical trends in location and demographic data to generate geofences to target locations around POIs.
• In an example, a coffee franchise may want to target certain demographic characteristics (target demographic parameters) of potential customers around each franchise location. A location-aware publication system can utilize general census-type demographic data to initially generate a set of geofences around (or associated with) each of the target POIs. In an example, the demographic characteristic might be average income, and the publication system can analyze demographic data in geographic areas surrounding a POI to determine the size and/or shape required for a geofence to encompass a certain predicted number or density of individuals with the target demographic (e.g., average income over $80,000/year). In certain examples, the geofence may not be centered on a particular POI, but rather allowed to float within a defined geographic area in order to best capture the target demographic. In these examples, the defined float geography can be centered or otherwise tied to one or more POIs, in order to ensure that the targeted audience is within a certain distance of an advertiser's physical locations.
• In these examples, the target demographics can include population density, average income, age ranges, percentage of male or females, average education level, active mobile device usage, or any other similar demographic characteristic. Geofences can also be generated based on other data susceptible to statistical analysis, such as competitors (locations or density) or WiFi hotspots, among other things. Some additional example target demographics can include: household income, marital status, sex, age, ethnicity, race, profession, average number of children, no children, median age, and male/female median age, among other things. Data sources for demographic data can include United States government collected census data, such as is available within a ZIP code database (from ZIP-CODES.COM, www.zip-codes.com/zip-code-database.asp (last visited Dec. 5, 2012)).
• In certain examples, statistical dynamic geofences can be generated and subsequently updated based on one or more target parameters. Referring back to the coffee franchise example, once an initial geofence has been generated and used to target distribution of a mobile advertisement, response results to the advertisement can be monitored and analyzed to update subsequent geofences for targeting future advertisement distribution. For example, the publication system can monitor click-throughs (or similar indications of interest in the distributed advertisement) and correlate the click-throughs with demographic data to determine whether the advertisement is reaching the target audience. Based on analysis of the click-through-related demographic data, the size or shape of the geofence can be updated in an attempt to increase the predicted number of target recipients matching a certain characteristic.
• In other examples, demographic data analysis may determine that the size or shape of a geofence should shift over the course of a day. For example, between the hours of 7:00 AM and 9:00 AM, the demographic data may indicate that target population density is high, allowing for a small radius geofence to be used in delivering targeted publications (e.g., advertisements or coupon offers). However, between 9:01 AM and 3:00 PM, the demographic data may indicate that a much larger radius needs to be considered to capture a similar potential audience. In this example, the dynamic geofence may change in size depending upon time of day of distribution by the publication system.
Example System
• FIG.1 is a block diagram depicting asystem100 for using statistical dynamic geofences to assist in targeted publication distribution, according to an example embodiment. In an example,system100 can includeusers110A-110N (collectively referred to as either user110 or users110 depending upon context) and a network-basedpublication system120. In an example, theusers110A-110N can connect to the network-basedpublication system120 viamobile devices115A-115N (collectively referred to as mobile device115).Users110A-110N can also connect to the network-basedpublication system120 viaclients140A-140N (collectively referred to as client140 or clients140). In certain examples, users110 can receive publications, onmobile devices115 or clients140, from the network-basedpublication system120 transmitted overnetwork105, but the users110 may not otherwise make any sort of direct connection with the network-basedpublication system120.
• In an example, the users110 can configure an account on the network-basedpublication system120. The account can be accessed by a user, such asuser110A, usingmobile device115A orclient140A, ifuser110A meets the specified access criteria or rules. In an example, the access rules can include user identification and/or mobile device identification. A user account on the network-basedpublication system120 can allow the user to define specific POIs of interest or provide other user data that can be used by the network-basedpublication system120 for targeting publications. In some examples, the network-basedpublication system120 can monitor user behavior and create geofences based on past and predicted user behaviors. In certain examples, the network-basedpublication system120 can be used by merchants as a location-based advertising platform, where users, such as users110, opt-in to location-based advertisements. For example, Best Buy (of Minneapolis, Minn.) may use the network-basedpublication system120 to provide location-based advertising to users110 viamobile devices115. In this example, the network-basedpublication system120 can use statistical dynamic geofences, as discussed herein, to target a geographic area that is likely to include a segment of users110 that meet a target demographic parameter. In this example, Best Buy would define an advertising campaign that includes a target demographic and a list of POIs relevant to the campaign.
Example Operating Environment
• FIG.2 is a block diagram illustrating anenvironment200 for operating amobile device115, according to an example embodiment. Theenvironment200 is an example environment within which methods for using statistical dynamic geofences can be implemented. Theenvironment200 can include amobile device115, acommunication connection210, anetwork220,servers230, acommunication satellite270, amerchant server280, and adatabase290. Theservers230 can optionally include location based service application (LBS)240,location determination application250,publication application260, andgeofence application265. Thedatabase290 can optionally includedemographic data292, user profiles294, and/orlocation history296. Themobile device115 represents one example device that can be utilized by a user to receive publications. Themobile device115 may be any of a variety of types of devices (for example, a cellular telephone, a personal digital assistant (PDA), a Personal Navigation Device (PND), a handheld computer, a tablet computer, a notebook computer, or other type of movable device). Themobile device115 may interface via aconnection210 with acommunication network220. Depending on the form of themobile device115, any of a variety of types ofconnections210 andcommunication networks220 may be used.
• For example, theconnection210 may be Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or other type of cellular connection.Such connection210 may implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1xRTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, or other data transfer technology (e.g., fourth generation wireless, 4G networks). When such technology is employed, thecommunication network220 may include a cellular network that has a plurality of cell sites of overlapping geographic coverage, interconnected by cellular telephone exchanges. These cellular telephone exchanges may be coupled to a network backbone (for example, the public switched telephone network (PSTN), a packet-switched data network, or other types of networks).
• In another example, theconnection210 may be a Wi-Fi or IEEE 802.11x type connection, a Worldwide Interoperability for Microwave Access (WiMAX) connection, or another type of wireless data connection. In such an embodiment, thecommunication network220 may include one or more wireless access points coupled to a local area network (LAN), a wide area network (WAN), the Internet, or other packet-switched data network.
• In yet another example, theconnection210 may be a wired connection, for example an Ethernet link, and the communication network may be a LAN, a WAN, the Internet, or other packet-switched data network. Accordingly, a variety of different configurations are expressly contemplated.
• A plurality ofservers230 may be coupled via interfaces to thecommunication network220, for example, via wired or wireless interfaces. Theseservers230 may be configured to provide various types of services to themobile device115. For example, one ormore servers230 may executeLBS applications240, which interoperate with software executing on themobile device115, to provide LBSs to a user. LBSs can use knowledge of the device's location, and/or the location of other devices, to provide location-specific information, recommendations, notifications, interactive capabilities, and/or other functionality to a user. For example, anLBS application240 can provide location data to a network-basedpublication system120, which can then be used to provide location-aware publications from the network-basedpublication system120, whereservers230 can be operating with the network-basedpublication system120. Knowledge of the device's location, and/or the location of other devices, may be obtained through interoperation of themobile device115 with alocation determination application250 executing on one or more of theservers230. Location information may also be provided by themobile device115, without use of a location determination application, such asapplication250. In certain examples, themobile device115 may have some limited location determination capabilities that are augmented by thelocation determination application250. In some examples, theservers230 can also includepublication application260 for providing location-aware publication of data such as advertisements or offers. In certain examples, location data can be provided to thepublication application260 by thelocation determination application250. In some examples, the location data provided by thelocation determination application250 can include merchant information (e.g., identification of a retail location). In certain examples, thelocation determination application250 can receive signals via thenetwork220 to further identify a location. For example, a merchant may broadcast a specific IEEE 802.11 service set identifier (SSID) that can be interpreted by thelocation determination application250 to identify a particular retail location. In another example, the merchant may broadcast an identification signal via radio-frequency identification (RFID), near-field communication (NFC), or a similar protocol that can be used by thelocation determination application250. In addition to examples using these various mechanisms to identify a particular location, these mechanisms (e.g., SSIDs, RFIDs, NFC, and so forth) can be used as secondary authentication factors, which are discussed in more detail below.
• In certain examples, thegeofence application265 can leverage theLBS application240 or thelocation determination application250 to assist in generating and/or updating geofences based on current or historical statistics.
Example Mobile Device
• FIG.3 is a block diagram illustrating themobile device115, according to an example embodiment. Themobile device115 may include aprocessor310. Theprocessor310 may be any of a variety of different types of commercially available processors suitable for mobile devices (for example, an XScale architecture microprocessor, a Microprocessor without Interlocked Pipeline Stages (MIPS) architecture processor, or another type of processor). Amemory320, such as a Random Access Memory (RAM), a Flash memory, or other type of memory, is typically accessible to the processor. Thememory320 may be adapted to store an operating system (OS)330, as well asapplication programs340, such as a mobile location enabled application that may provide LBSs to a user. Theprocessor310 may be coupled, either directly or via appropriate intermediary hardware, to adisplay350 and to one or more input/output (I/O)devices360, such as a keypad, a touch panel sensor, a microphone, and the like. Similarly, in some embodiments, theprocessor310 may be coupled to atransceiver370 that interfaces with anantenna390. Thetransceiver370 may be configured to both transmit and receive cellular network signals, wireless data signals, or other types of signals via theantenna390, depending on the nature of themobile device115. In this manner, theconnection210 with thecommunication network220 may be established. Further, in some configurations, aGPS receiver380 may also make use of theantenna390 to receive GPS signals.
Example Platform Architecture
• FIG.4 is a block diagram illustrating a network-basedsystem400 for using statistical dynamic geofences to assist in targeted publication distribution, according to an example embodiment. The block diagram depicts a network-based system400 (in the exemplary form of a client-server system), within which an example embodiment can be deployed. Anetworked system402 is shown, in the example form of a network-based location-aware publication or payment system, that provides server-side functionality, via a network404 (e.g., the Internet or WAN) to one ormore client machines410,412.FIG.4 illustrates, for example, a web client406 (e.g., a browser, such as the Internet Explorer browser developed by Microsoft Corporation of Redmond, Wash.) and a programmatic client408 (e.g., PAYPAL payments smart phone application from PayPal, Inc. of San Jose, Calif.) executing onrespective client machines410 and412. In an example, theclient machines410 and412 can be in the form of a mobile device, such asmobile device115. In yet another example, theprogrammatic client408 can be the RedLaser mobile shopping application from eBay, Inc. of San Jose, Calif.
• An Application Programming Interface (API)server414 and aweb server416 are coupled to, and provide programmatic and web interfaces respectively to, one ormore application servers418. Theapplication servers418 host one or more publication modules420 (in certain examples, these can also include commerce modules, advertising modules, and marketplace modules, to name a few),payment modules422, andgeofencing modules432. Theapplication servers418 are, in turn, shown to be coupled to one ormore database servers424 that facilitate access to one ormore databases426. In some examples, theapplication server418 can access thedatabases426 directly without the need for adatabase server424.
• Thepublication modules420 may provide a number of publication functions and services to users who access thenetworked system402. Thepayment modules422 may likewise provide a number of payment services and functions to users. Thepayment modules422 may allow users to accumulate value (e.g., in a commercial currency, such as the U.S. dollar, or a proprietary currency, such as “points”) in accounts, and then later to redeem the accumulated value for products (e.g., goods or services) that are advertised or made available via thevarious publication modules420, within retail locations, or within external online retail venues. Thepayment modules422 can also be configured to facilitate payment processing based on geofence detection and work in conjunction with thegeofence modules432. Thegeofencing modules432 may provide generation and updating of statistical dynamic geofences, among other things. While thepublication modules420,payment modules422, andgeofencing modules432 are shown inFIG.4 to all form part of thenetworked system402, it will be appreciated that, in alternative embodiments, thepayment modules422 may form part of a payment service that is separate and distinct from thenetworked system402.
• Further, while thesystem400 shown inFIG.4 employs client-server architecture, the present invention is of course not limited to such an architecture, and could equally well find application in a distributed, or peer-to-peer, architecture system, for example. Thevarious publication modules420,payment modules422, andgeofencing modules432 could also be implemented as standalone systems or software programs, which do not necessarily have networking capabilities.
• Theweb client406 accesses thevarious publication modules420,payment modules422, andgeofencing modules432 via the web interface supported by theweb server416. Similarly, theprogrammatic client408 accesses the various services and functions provided by thepublication modules420,payment modules422, andgeofencing modules432 via the programmatic interface provided by theAPI server414. Theprogrammatic client408 may, for example, be a smart phone application (e.g., the PAYPAL payments application) that enables users to process payments directly from their smart phones leveraging user profile data and current location information provided by the smart phone or accessed over thenetwork404.
• FIG.4 also illustrates athird party application428, executing on a thirdparty server machine440, as having programmatic access to thenetworked system402 via the programmatic interface provided by theAPI server414. For example, thethird party application428 may, utilizing information retrieved from thenetworked system402, support one or more features or functions on a website hosted by the third party. The third party website may, for example, provide one or more promotional, marketplace or payment functions that are supported by the relevant applications of thenetworked system402. Additionally, the third party website may provide merchants with access to thegeofencing modules432 for advertising or marketing purposes (e.g., location-aware publication targeting).
Example Geofencing Modules
• FIG.5 is a block diagram illustratinggeofencing modules432, according to an example embodiment. In this example, thegeofencing modules432 can include arules engine505, acommunication module510, ageneration module520, adata collection module530, and alocation module540. In an example, thegeofencing modules432 can accessdatabase426 to store and/or retrieve generation rules, user profile data, location data, and demographic data, as well as other information, to enable statistical dynamic geofencing.
• In an example, therules engine505 can be configured to manage and evaluate rules controlling geofence generation and updating. Rules can be provided by an advertiser for each campaign run on thenetworked system402. As discussed above, one of the “rules” can define the type of statistical analysis as well as the target demographic (or similar data set) to be used in generating or updating a geofence. For example, a geofence rule may correlate the geofence radius to population density of the target geographical area. In this example, the lower the population density, the larger the radius of the resulting geofence. Accordingly, for a franchisee with locations in different geographic areas, such a rule can allow for locations in low density areas and locations in high density areas to still fall within a single advertising campaign while maintaining a similar average number of impressions for distributed advertisements.
• In an example, thecommunication module510 can be configured to manage communications between thegeofencing modules432 and a user, where the user is communicating via themobile device115 or the client140. Thecommunication module510 can also be configured to manage communications between thegeofencing modules432 and a merchant or advertiser.
• In an example, thegeneration module520 is configured to generate and update geofences according to information provided by modules, such as thedata collection module530, thelocation module540, and therules engine505.
• In an example, thedata collection module530 is configured to collect data related to a publication or advertising campaign. In certain examples, thedata collection module530 can collect data detailing the results of an advertisement distribution, such as number of impressions and click-throughs. Impressions can indicate the number of times a mobile device displayed the advertisement, while click-throughs can indicate the number of users that interacted with an advertisement (e.g., clicked the ad). In certain examples, thedata collection module530 can aggregate results data and, in some cases, correlate demographic data related to the users with the advertising results.
• In an example, thelocation module540 is configured to receive location data from a mobile device, such asmobile device115, and determine from the location data a current physical location, which may include reference to landmarks or other sites of interest. In some examples, thelocation module540 can receive GPS-type coordinates (e.g., longitude and latitude), which can be used to establish a current location associated with a mobile device (and, thus, a user of the mobile device). Using the longitude and latitude coordinates, thelocation module540 can determine if the current location is within a geofence, for example. In another example, some merchants may broadcast specific wireless network signals that can be received by a mobile device, such asmobile device115. Once received, themobile device115 can include programming or circuitry to translate the signal into a specific location, or themobile device115 can simply retransmit the unique signal to thelocation module540. In an example, a merchant location can transmit a unique SSID, which thelocation module540 can be programmed to interpret as identifying a specific merchant location. In another example, the merchant may broadcast a unique SSID within all of its locations and thelocation module540 can be programmed to use a combination of the unique SSID and other location data (e.g., GPS coordinates or cell tower locations) to identify a specific location
• Additional details regarding the functionality provided by thegeofencing modules432 are detailed in reference toFIGS.6-8.
Example Dynamic Geofences
• FIG.6 is a diagram illustrating geofence updating via statistical analysis, according to an example embodiment. The map display600 includes a number of geofences (610-630) and highlighted POIs (A-J). In this example, three geofences are illustrated including two dynamic geofences610 (610A,610B) and620 (620A,620B) and one static geofence630. All of the illustrated geofences can be used to target publications to recipients within a limited geographic area. Further, even geofence630, which is illustrated as a static or unchanging, can be updated to change its size or shape at some future point in time.
• In an example,geofence610A can represent an initial state of geofence610 generated around POI C. Geofence610 represents a simple circular geofence centered on POI C. In this example, geofence610 can include a geofence parameter defining the radius of the dynamic geofence. In an example, the geofence parameter for geofence610 can be based on a target demographic, such as population density. In this example, the geofence610 can shift between a first geofence parameter value resulting ingeofence610A and a second geofence parameter value resulting ingeofence610B due to shifts in the target demographic parameter. For example, if the target demographic parameter is population density, the shift may occur over the course of a day in the case of a downtown business district or over the course of the year for a vacation or retirement community.
• In another example, geofence620 represents a more complex geofence laid out to cover a particular geographic area, which may correlate to certain traffic patterns or local retail locations, among other things. Geofence620 can be defined by a series of coordinates (latitude/longitude pairs), city block designations, or street intersections, among other things. Geofence620 also illustrates the potential for a geofence to shift in shape due to changes in related demographics or other statistical data driving the particular shape. For example, an advertiser may want to avoid areas of a city that include competing locations, and such locations may change over time. In an example, a food truck operator may request that the network-basedpublication system120 run a location-aware advertising campaign within the operating area for the food truck. Geofence620 can illustrate twodifferent operating areas620A and620B, which may represent areas targeted on different days of the week or a shift in areas based on changes in competitor locations. WhileGeofences620A and620B overlap, as illustrated inFIG.6, there is no requirement for overlap between iterations of a dynamic geofence.
Example Methods
• FIG.7 is a flowchart illustrating amethod700 of generating and using statistical dynamic geofences to assist in targeted publication distribution, according to an example embodiment. In an example, themethod700 can include operations for: receiving a location-based campaign request at710, analyzing demographic data at720, determining a geofence parameter at730, generating a geofence at740, and distributing advertisements at750.
• In an example, themethod700 can begin at710 with thenetworked system402 receiving a location-based campaign request from an advertiser. In this example, the location-based campaign request can include a list of POIs and a target demographic parameter. The target demographic parameter can control at least one aspect of a geofence to be used for targeting publications around a POI.
• At720, themethod700 can continue with thenetworked system402 analyzing demographic data related to the target demographic parameter. For example, if the target demographic parameter is average income, thenetworked system402 can analyze demographic data from geographic areas around each POI in the list of POIs to determine the density of individuals within that geographic area that meet or exceed the target demographic parameter. A target demographic parameter can include population density, competitive POIs, income level, gender density, or age ranges, among other things. Further, in certain examples, multiple target demographic parameters may be defined and analyzed.
• At730, themethod700 can continue with thenetworked system402 determining a geofence parameter, such as a radius, based on the analysis of the demographic data. In the average income example, the geofence parameter can be tied to the determined (or predicted) density of individuals meeting or exceeding the target average income. In areas with a high density, the geofence parameter may be reduced (e.g., a smaller radius geofence may be centered on a POI in that geographic area); conversely, if the density is low, the geofence parameter may be increased.
• At740, themethod700 can continue with thenetworked system402 generating a geofence around at least one of the POIs in the list of POIs. As discussed above, the geofence generation can be based at least in part on the geofence parameter. In certain examples, the geofence parameter may include a list of coordinates, thereby allowing the geofence parameter to alter the size and shape of the generated geofence.
• At750, themethod700 can conclude with thenetworked system402 distributing location-aware advertisements (or similar publications) within the geofence generated around the POI. In an example, the advertisements can be distributed to a plurality of mobile devices, such asmobile devices115, located within the geofence area. Thenetworked system402 can use any of the methods discussed above, or known in the art, to determine the locations of themobile devices115.
• Though arranged serially in the example ofFIG.7, other examples may reorder the operations, omit one or more operations, and/or execute two or more operations in parallel using multiple processors or a single processor organized as two or more virtual machines or sub-processors. Moreover, still other examples can implement the operations as one or more specific interconnected hardware or integrated circuit modules with related control and data signals communicated between and through the modules. Thus, any process flow is applicable to software, firmware, hardware, and hybrid implementations.
• FIG.8 is a flowchart illustrating amethod800 of updating statistical dynamic geofences to refine targeted publication distribution, according to an example embodiment. As illustrated inFIG.8, in this example, the process illustrated bymethod800 can occur after the process of generating a geofence discussed with respect toFIG.7. In this example, themethod800 can include operations such as: receiving campaign results data at810, analyzing the campaign results data at820, updating the geofence parameter at830, updating the geofence at840, and distributing advertisements within the updated geofence at850.
• In an example, themethod800 can begin at810 with thenetworked system402 receiving campaign results data. The campaign results data can be collected based on the initial distribution of a publication (e.g., advertisement) within the initially generated geofence. At820, themethod800 can continue with thenetworked system402 analyzing the campaign results data in reference to a target demographic parameter or other campaign driven parameter. In an example, the campaign results data can be correlated with demographic information related to the users targeted by the initial publication campaign.
• At830, themethod800 can continue with thenetworked system402 updating the geofence parameter based at least in part on the analysis of the campaign results data. In an example, the geofence parameter can be linked to the density of males over the age of 35, and analysis of the campaign result data may indicate that the projected density is different than the original demographic data analysis indicated. Accordingly, thenetworked system402 can adjust to the detected change.
• At840, themethod800 can continue with thenetworked system402 updating the geofence around the POI based on the updated geofence parameter. At850, themethod800 can conclude with thenetworked system402 distributing a second wave of advertising to mobile devices detected within the updated geofence area.
• Though arranged serially in the example ofFIG.8, other examples may reorder the operations, omit one or more operations, and/or execute two or more operations in parallel using multiple processors or a single processor organized as two or more virtual machines or sub-processors. Moreover, still other examples can implement the operations as one or more specific interconnected hardware or integrated circuit modules with related control and data signals communicated between and through the modules. Thus, any process flow is applicable to software, firmware, hardware, and hybrid implementations.
Modules, Components and Logic
• Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied on a machine-readable medium or in a transmission signal) or hardware modules. A hardware module is a tangible unit capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client, or server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein.
• In various embodiments, a hardware module may be implemented mechanically or electronically. For example, a hardware module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC)) to perform certain operations. A hardware module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.
• Accordingly, the term “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily configured (e.g., programmed) to operate in a certain manner and/or to perform certain operations described herein. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where the hardware modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware modules at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.
• Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules may be regarded as being communicatively coupled. Where multiple of such hardware modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connects the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules may also initiate communications with input or output devices and can operate on a resource (e.g., a collection of information).
• The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules.
• Similarly, the methods described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or more processors or processor-implemented modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations.
• The one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., APIs).
Electronic Apparatus and System
• Example embodiments may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of these. Example embodiments may be implemented using a computer program product, for example, a computer program tangibly embodied in an information carrier, for example, in a machine-readable medium for execution by, or to control the operation of, data processing apparatus, for example, a programmable processor, a computer, or multiple computers.
• A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, subroutine, or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a communication network.
• In example embodiments, operations may be performed by one or more programmable processors executing a computer program to perform functions by operating on input data and generating output. Method operations can also be performed by, and apparatus of example embodiments may be implemented as, special purpose logic circuitry (e.g., a FPGA or an ASIC).
• The computing system 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. In embodiments deploying a programmable computing system, it will be appreciated that both hardware and software architectures require consideration. Specifically, it will be appreciated that the choice of whether to implement certain functionality in permanently configured hardware (e.g., an ASIC), in temporarily configured hardware (e.g., a combination of software and a programmable processor), or a combination of permanently and temporarily configured hardware may be a design choice. Below are set out hardware (e.g., machine) and software architectures that may be deployed, in various example embodiments.
Example Machine Architecture and Machine-Readable Medium
• FIG.9 is a block diagram of a machine in the example form of acomputer system900 within which instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in a server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a PDA, a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.
• Theexample computer system900 includes a processor902 (e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), amain memory904 and astatic memory906, which communicate with each other via abus908. Thecomputer system900 may further include a video display unit910 (e.g., a liquid crystal displays (LCD) or a cathode ray tube (CRT)). Thecomputer system900 also includes an alpha-numeric input device912 (e.g., a keyboard), a cursor control (user interface (UI) navigation) device914 (e.g., a mouse), adisk drive unit916, a signal generation device918 (e.g., a speaker) and anetwork interface device920.
Machine-Readable Medium
• Thedisk drive unit916 includes a machine-readable medium922 on which is stored one or more sets of instructions and data structures (e.g., software)924 embodying or used by any one or more of the methodologies or functions described herein. Theinstructions924 may also reside, completely or at least partially, within themain memory904,static memory906, and/or within theprocessor902 during execution thereof by thecomputer system900, with themain memory904 and theprocessor902 also constituting machine-readable media.
• While the machine-readable medium922 is shown in an example embodiment to be a single medium, the term “machine-readable medium” may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more instructions or data structures. The term “machine-readable medium” shall also be taken to include any tangible medium that is capable of storing, encoding or carrying instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present invention, or that is capable of storing, encoding or carrying data structures used by or associated with such instructions. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories and optical and magnetic media. Specific examples of machine-readable media include non-volatile memory, including by way of example, semiconductor memory devices (e.g., Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM)) and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.
Transmission Medium
• Theinstructions924 may further be transmitted or received over acommunications network926 using a transmission medium. Theinstructions924 may be transmitted using thenetwork interface device920 and any one of a number of well-known transfer protocols (e.g., HTTP). Examples of communication networks include a LAN, a WAN, the Internet, mobile telephone networks, Plain Old Telephone (POTS) networks, and wireless data networks (e.g., WiFi and WiMax networks). The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such software.
• Although an embodiment has been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the invention. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. The accompanying drawings that form a part hereof, show by way of illustration, and not of limitation, specific embodiments in which the subject matter may be practiced. The embodiments illustrated are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed herein. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. This Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.
• Such embodiments of the inventive subject matter may be referred to herein, individually and/or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Thus, although specific embodiments have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description.
• All publications, patents, and patent documents referred to in this document are incorporated by reference herein in their entirety, as though individually incorporated by reference. In the event of inconsistent usages between this document and those documents so incorporated by reference, the usage in the incorporated reference(s) should be considered supplementary to that of this document; for irreconcilable inconsistencies, the usage in this document controls.
• In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one, independent of any other instances or usages of “at least one” or “one or more.” In this document, the term “or” is used to refer to a nonexclusive or, such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Also, in the following claims, the terms “including” and “comprising” are open-ended; that is, a system, device, article, or process that includes elements in addition to those listed after such a term in a claim are still deemed to fall within the scope of that claim. Moreover, in the following claims, the terms “first,” “second,” and “third,” and so forth are used merely as labels, and are not intended to impose numerical requirements on their objects.
• The Abstract of the Disclosure is provided to comply with 37 C.F.R. § 1.72(b), requiring an abstract that will allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.

Claims (20)

The claimed invention includes:

1. A method comprising:

obtaining demographic data for a geographic area surrounding a point of interest (POI), the demographic data including data related to a number of users located within the geographic area at different times;

determining, based on the demographic data for the geographic area, a first population density of users that are located within the geographic area during a first portion of a day, and a second population density of users that are located within the geographic area during a second portion of the day; and

controlling a geofence to have a first size around the POI during the first portion of the day based on the first population density and to have a second size around the POI during the second portion of the day based on the second population density.

2. The method ofclaim 1, further comprising transmitting a publication to mobile devices located within the geofence during the first portion of the day and during the second portion of the day.

3. The method ofclaim 2, wherein the first size and the second size of the geofence is based at least in part on a requested target number of users to receive the publication.

4. The method ofclaim 3, wherein the publication is transmitted to a first group of mobile devices located within the geofence during the first portion of the day, and wherein the publication is transmitted to a second group of mobile devices located within the geofence during the second portion of the day.

5. The method ofclaim 4, wherein the first group of mobile devices is different than the second group of mobile devices.

6. The method ofclaim 3, further comprising updating the first size or the second size in response to determining that a number of users that received the publication is less than the requested target number of users.

7. The method ofclaim 2, further comprising analyzing click-through data to determine user interaction with the publication, and updating the first size or the second size in response to analyzing the click-through data in order to increase a number of users that received the publication.

8. The method ofclaim 2, wherein the publication comprises a location-aware advertisement.

9. A server comprising:

at least a memory and a processor configured to:

obtain demographic data for a geographic area surrounding a point of interest (POI), the demographic data including data related to a number of users located within the geographic area at different times;

determine, based on the demographic data for the geographic area, a first population density of users that are located within the geographic area during a first portion of a day, and a second population density of users that are located within the geographic area during a second portion of the day; and

control a geofence to have a first size around the POI during the first portion of the day based on the first population density and to have a second size around the POI during the second portion of the day based on the second population density.

10. The server ofclaim 9, wherein the memory and the processor are further configured to transmit a publication to mobile devices located within the geofence during the first portion of the day and during the second portion of the day.

11. The server ofclaim 10, wherein the first size and the second size of the geofence is based at least in part on a requested target number of users to receive the publication.

12. The server ofclaim 11, wherein the publication is transmitted to a first group of mobile devices located within the geofence during the first portion of the day, and wherein the publication is transmitted to a second group of mobile devices located within the geofence during the second portion of the day.

13. The server ofclaim 12, wherein the first group of mobile devices is different than the second group of mobile devices.

14. The server ofclaim 11, further comprising updating the first size or the second size in response to determining that a number of users that received the publication is less than the requested target number of users.

15. The server ofclaim 10, further comprising analyzing click-through data to determine user interaction with the publication, and updating the first size or the second size in response to analyzing the click-through data in order to increase a number of users that received the publication.

16. The server ofclaim 10, wherein the publication comprises a location-aware advertisement.

17. A non-transitory computer-readable medium storing instructions that, when executed by one or more computer processors of a server, cause the server to perform operations comprising:

obtaining demographic data for a geographic area surrounding a point of interest (POI), the demographic data including data related to a number of users located within the geographic area at different times;

determining, based on the demographic data for the geographic area, a first population density of users that are located within the geographic area during a first portion of a day, and a second population density of users that are located within the geographic area during a second portion of the day; and

controlling a geofence to have a first size around the POI during the first portion of the day based on the first population density and to have a second size around the POI during the second portion of the day based on the second population density.

18. The non-transitory computer-readable medium ofclaim 17, wherein the operations further comprise transmitting a publication to mobile devices located within the geofence during the first portion of the day and during the second portion of the day.

19. The non-transitory computer-readable medium ofclaim 18, wherein the first size and the second size of the geofence is based at least in part on a requested target number of users to receive the publication.

20. The non-transitory computer-readable medium ofclaim 19, wherein the publication is transmitted to a first group of mobile devices located within the geofence during the first portion of the day, and wherein the publication is transmitted to a second group of mobile devices located within the geofence during the second portion of the day.

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