Amazon Tracking Patent

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c12) United States PatentScofield et al.

(54) SYSTEM AND METHOD FOR PROVIDINGADVERTISEMENT BASED ON MOBILEDEVICE TRAVEL PATTERNS

(75) Inventors: Christopher L. Scofield, Seattle, WA(US); Elmore Eugene Pope,Sammamish, WA (US); Brad E.Marshall, Bainbridge Island, WA (US);Eric B. Merritt, Seattle, WA (US)

(73) Assignee: Amazon Technologies, Inc., Reno, NV(US)( *) Notice: Subject to any disclaimer, the term of thispatent is extended or adjusted under 35U.S.C. 154(b) by 709 days.(21) Appl. No.: 11/693,363(22) Filed: Mar. 29, 2007

(63)

(51)

(52)(58)

(56)

Related U.S. Application DataContinuation-in-part of application No. 11/683,849,filed on Mar. 8, 2007.Int. Cl.H04W 24100 (2009.01)G06Q 30100 (2006.01)H04M 3/42 (2006.01)U.S. Cl. ............... 455/456.1; 455/414.1; 455/456.3;705/14.71Field of Classification Search ............... 455/414.1,455/414.2, 456.1; 705/14See application file for complete search history.

References CitedU.S. PATENT DOCUMENTS

6,144,336 A6,343,317 B16,801,855 B16,765,492 B2

1112000 Preston et al.112002 Glorikian10/2002 Cuchlinski, Jr.7/2004 Harris

111111 1111111111111111111111111111111111111111111111111111111111111US008073460B 1

(10) Patent No.: US 8,073,460 BlDec. 6, 201145) Date of Patent:

6,801,778 B26,806,830 B26,903,685 B12002/0002504 A1 *2002/0050927 A1 *2002/0077130 A1 *2002/0094787 A12002/0111154 A12002/0183059 A12003/0126150 A12003/0200128 A1 *2004/0044574 A1 *2004/0127217 A1

10/2004 Koorapaty10/2004 Panasik6/2005 Arndt112002 Engel eta!. ..................... 705/265/2002 De Moerloose eta!. ..... 340/5396/2002 Owensb y ...................... 455/4667/2002 Avnet eta!.8/2002 Eldering eta!.12/2002 Noreen eta!.7/2003 Chan10/2003 Doherty ............................ 705/83/2004 Cochran eta!. ................. 705/147/2004 Aoki eta!.(Continued)

OTHER PUBLICATIONSU.S. Appl. No. 111683,849, filed Mar. 8, 2007.

(Continued)Primary Examiner- Nick CorsaroAssistantExaminer- Edd Rianne Plata(74) Attorney, Agent, or Firm- Robert C. Kowert;Meyertons, Hood, Kivlin, Kowert & Goetze!, P.C.(57) ABSTRACTMobile device users may be tracked either via mobile-signaltriangulation or via Global Positioning Satellite information.A mobile device user' s recent movements may be analyzed todetermine trails or traffic patterns for device user amongvarious locations. Mobile device trail information, either foran individual user or aggregated for multiple users, may beanalyzed to determine a next destination for the user. Electronic advertising content, such as advertisements, couponsand/or other communications, associated with the next destination may be sent to an electronic device likely to be viewedby the mobile device user. Additionally, the identity of themobile device user may be known and the advertisements orcoupons may be tailored according to demographic information regarding the mobile device user. In addition, destinations may be recommended to mobile device users based onthe recent locations the users have visited.

36 Claims, 9 Drawing Sheets

mobile service)+----+! providertrail

information.1.8ll 4=

public displaydevice(s).11Q

Global Positioning Salellite(s)130

mobile device(s) 1.1.0.

communicationtower(s)140


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US 8,073,460 BlPage 2

U.S. PATENT DOCUMENTS 2007/0105536 A1 5/2007 Tingo2005/0049789 A12005/0064851 A1 *2006/0036366 A12006/0040710 A12006/0053048 A12006/0064346 A1 *2006/0265281 A12007/0010942 A1 *

3/2005 Kelly eta!.3/2005 Malackowski eta!. .... 455/414.12/2006 Kelly et a!.2/2006 Ruetschi eta!.3/2006 Tandetnik3/2006 Steenstra et al ................. 705/141112006 Sprovie ri et a!.112007 Bill ......... ............... ....... 7011209

2007/0270132 A1 * 1112007 Poosa la .............. ........ 455/414.22008/0046324 A1 * 2/2008 Bailey eta!. .................... 705/142008/0228568 A1 * 9/2008 Williams eta!. ................ 705/14OTHER PUBLICATIONS

Office Action from U.S. Appl. No. 111683,849, mailed Oct. 7, 2009.* cited by examiner


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U.S. Patent

traffic patternanalysis system100traffic analysisengine150

trailinformation180

public displaydevice(s)170

Dec. 6, 2011 Sheet 1 of9

lobal Positioning Satellite(s)130

positionreporting logic160

mobile device(s) 11 0

FIG. 1

US 8,073,460 Bl

mobile serviceprovider1.95.

communicationtower(s)140


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U.S. Patent Dec. 6, 2011 Sheet 2 of9 US 8,073,460 Bl

200\

FIG. 2


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U.S. Patent Dec. 6, 2011 Sheet 3 of9

determine one or more nextdestinations for a user of amobiledevice based on one or more locationsvisited by the mobile device user.300

determine advertising contentassociated with the next destinations320

yes display onmobile device?330no

US 8,073,460 Bl

communicate the advertisingcontent to the mobile device340

communicate the advertising content toone or more public display devices350

FIG. 3


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advertising content400\

mobile device/110

10% off all clothing atRaves and RagsYou're heading there

now!Just show thismessage to thecashier.

>- - - -1 -0 0800CDCDCD000C)00

FIG. 4A


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U.S. Patent

advertising content400

Dec. 6, 2011 Sheet 5 of9 US 8,073,460 Bl

\\.,

public display device/170

..........

peronalization430Hey J o h n , ~ f--10% off all clothing atRaves and Rags

You're heading there now!

\

Just mentionthis messageto the cashier.

u s e r w t h ~ mobile device

FIG. 48


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location 600 / location 620/advertising / advertisingcontent content610 630

location680location 640 --locat ion 660advertising / advertisingontent content650 670

advertisingcontent -r --55FIG. 6


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U.S. Patent Dec. 6, 2011 Sheet 8 of9

determine one or more next destinations foramobile device user based on one or morelocations visited by the mobile device user

700

receive bids for communicating advertisingcontent for at least one of the one or morenext destinations

yes

720

display onmobile device?730

no

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communicate advertising content regardingthe next destination with the highest bid tothe mobile device of the mobile phone usercommunicate advertising content regardingthe next destination with the highest bid toone or more public display devices

75040

FIG. 7


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Computer system 900

Processor Processor Processor910a 910b . .. 910n

1/0 interface930

System memory Network920Programinstructions925

FIG. 8

interface940

to/from communicationdevices or control system


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SYSTEM AND METHOD FOR PROVIDINGADVERTISEMENT BASED ON MOBILE

DEVICE TRAVEL PATTERNSThis application is a Continuation-In-Part of U.S. patentapplication Ser. No. 11/683,849 titled, "Sys tem and Method

for Analyzing Mobile Device Travel Patterns," filed Mar. 8,2007, whose inventors are Christopher L. Scofield, ElmoreEugene Pope, Br ad E. Marshall and Eric B. Merritt, which isherein incorporated by reference in its entirety.BACKGROUND OF THE INVENTION

1. Field of the InventionThis invention relates to mobil e device u ser traffic patternsand, more particularly, to directing advertising to mobiledevice users corresponding to predicted future destinations ofthe mobile device users.2. Description of the Related ArtMobile phones have gone from being rare and expensivepieces of equipment used primarily by the business elite, to apervasive low-cost personal item. In many countries, mobile

phones now outnumber land-line telephones, with mostadults and many children now owning mobile phones. In theUnited States, 50% of children own mobile phones. It is notuncommo n for people to simply own a mobile phone instead

2content to the mobile device users based on the users' predicted destinations. For example, location dependent advertising content may be provided to mobile device users basedon a current and/or predicted location that the mobile deviceuser is likely to visit. In some embodiments, mobile deviceusers' current and past travel patterns may be analyzed todetermine a predicted next destination. For instance, by analyzing the recent movements of a mobile device user amongstores in a shopping mall, it may be determined that a par-

10 ticular store is a predicted next destination for the mobiledevice user. Thus, advertising content for the predicted destination, such as coupons, may be sent to the mobile deviceuser.In some embodiments, a mobile device user's travel or

15 traffic patterns (e.g., a set oflocations and the order in whichthose location are visited) may be analyzed to predict a nextlikely location or destination. Various types of advertisingcontent, such as electronic coupons, and ot her advertisementsmay be directed to the mobile device user based on the pre-

20 dieted destination. Fo r example, a mobile device user may betracked as she shops at various stores in a shopping mall.Based on the stores she has recently visited, a traffic patternanalysis system may determine a next most likely store orother destination that the mobile device user may visit. The

25 system may then send advertisements, coupons, or othercommercial communication to the user's mobile device or toanother electronic display device, such as to offer a discountor other shopping benefit to the mobile device user if sheof a land-line for their residence. In some developing countries there is little existing fixed -line infrastructure and con

sequently mobile phone use has become widespread. In general, a mobile or cellular telephone is a long-range, portable 30electronic device for personal telecommunications over long(or short) distances. Most current mobile phones connect to acellular network of base stations (cell sites), which is in turninterconnected to the public switched telephone network(PSTN) (the exception are satellite phones).

visits the predi cted destination.For instance, in one embodiment, a mobile device user maybe tracked as she visits several of the clothing stores in ashopping mall. Based on the type and location of the storesvisited, the system may determine that she is likely to visitanother clothing store in another part of he shopping mall. In

35 response to determining a store that the mobile device user islikely to visit, the system may send advertising content, suchas an electronic coupon good for 10% offany purchases madeat the store that day, to the mobile device user. Thus, themobile device user may be more likely to visit the store

With high levels of mobile telephone penetration, a mobileculture has evolved, where the phone becomes a key socialtool, and people rely on their mobile phone address book tokeep in touch with their friends. Many phones offer textmessaging services to increase the simplicity and ease oftexting on phones. Many people keep in touch using textmessaging, such as SMS, and a whole culture of"texting" hasdeveloped from this.

40 because of the added enticement of the discount.

Traditionally, commercial advertising has been concernedwith attempting to get the most consumers as possible to see 45the particular advertisement. Various media have been usedfor advertising over the years, such as, billboards, printedflyers, radio, cinema and television ads, web banners, webpopups, magazines, newspapers, and even the sides of buses,taxicab doors and roof mounts. Advertisers generally must 50select a static location at which to place their advertisementand hope that consumers hap pen upon them.Recently modern mobile phones or other mobile devicesmay be located either by cell-signal triangulation or throughGlobal Positioning Satellite (GPS) tracking. In general, 55mobile device service providers are increasingly required toprovide positioning information to support emergency services. When using cell-signal triangulation, mobile deviceusers can be tracked at all times regardless of whether a cellcall is underway. This is because t he mobile device performs 60a periodic connectivity check to the service provider. Thischeck registers the device relative to cell towers.

Mobile device directed advertising content may be used insituations other than retail shopping. For example, a mobil edevice user may be tracked while attending a large entertainment venue or sporting event and coupons advertising a discount at a restaurant that the mobile device user is likely tovisit based on the user's traffic or travel patterns at the enter-tainment venue or sporting event. Similarly, mobile deviceusers attending a large venue may be tracked and providedcoupons for vendors the mobile device users are likely to passbased on their recent travel patterns in and around the venue.In some embodiments, the advertising content, such ascoupons, discount offers, and other advertisements, may besent to the mobile device of he user. For example, advertisingcontent may be directed to the user's mobile phone. In otherembodiments, however, the advertising content may be sentand displayed on a separate electronic display device, such asa kiosk in a shopping mall that includes an electronic displaydevice. For example, an advertisement for a particular storedetermined to be a likely destination for a mobile user may bedisplayed on a wall mounted electronic display device in themall along a path the user is likely to take to the predicteddestination.

SUMMARYThe movements of mobile device users may be detected,recorded, tracked and analyzed in order to direct advertising

In some embodiments, the service may allow the destinations (store owners) to pay or bid to have advertising for their65 location communicated to the mobile device. For example,the system may determine more than one predicted destination and may allow each of the predicted destinations to bid


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direct advertising content to the mobile device users based onthe users' predicted destinations. In some embodiments,mobile device users' current and past traffic patterns may beanalyzed to determine a predicted next destination. Forinstance, by analyzing the recent movements of a mobiledevice user among stores in a shopping mall, it may be determined that a particular store is a predicted next destination forthe mobile device user. Thus, advertising content for thepredicted destination, such as coupons, may be sent, dis-

on placing advertising on the mobile device. In some embodiments, such bidding may occur in real time, such as by automated bidding software. In other embodiments, the cost of headvertising m ay be determined based on the likelihood thatthe mobile device user may travel to the particular destination. In other words, if previous traffic pattern analysis determines that the mobile device user is highly likely to go to aparticular destination, such as a particular store in a shoppingmall, the cost of placing an advertisement for that particulardestination on the mobile device may be more expensive thanifthere is a low probabil ity of he mobile device user going tothe particular destination.

10 played, or otherwise provided to the mobile device user.

BRIEF DESCRIPTION OF THE DRAWINGSAs used herein the term 'destination' is not intended tonecessarily convey any sort of finality. Instead, 'destination'is used merely to indicate a location to which a mobile deviceuser may travel. The mobile device user may also travel to

FIG. 1 is a logical block diagram illustrating various components of a system configured to analyze mobile deviceusers' traffic patterns and to determine next destinations forthe mobile device users to communicate advertising contentregarding the next destination to the mobile device user,according to one embodiment.

15 additional locations or destinations. Thus, as used herein, a'destination' is simply a location, that may or may not be afinal or intermediate location visited by a mobile device user.Additionally, as used herein the terms 'predicted destination','predicted next destination' and the like, are used to refer to aFIG. 2 illustrates one embodiment of a navigational patterninformation diagram representing mobile device user naviga

tion paths among locations.

20 location to which a mobile device user is more likely to visitthan another location and is not meant to necessarily implyany absolute probability of he mobile device user visiting thelocation.FIG. 1 is a logical block diagram illustrating various com-IG. 3 is a flowchart illustrating one embodiment of amethod for delivering advertising content to a mobile devicefor a next destination for mobile device user.FIG. 4A is a block diagram illustrating an example mobiledevice displaying advertising content for a determined nextdestination, according to one embodiment.FIG. 4B is a block diagram illustrating an example electronic display device displaying advertising content for adetermined next destination, according to one embodiment.

25 ponents of a system including traffic pattern analysis system100 (herein also referred to only as system 100) that, in someembodiments, ma y be configured to analyze traffic patterns(also referred to herein as trail or path information) for mobiledevice users in order to determine predicted destinations for

FIG. 5 illustrates an exemplary mobile device 110 displaying a user interface for allowing a user of he mobile device torequest a coupon and/or recommended destination.

30 the mobile device users and to communicate advertising,coupons and/or other information regarding the predicteddestination to the mobile device user.

FIG. 6 is a block diagram illustrating the logical arrange- 35ment of advertising content for locations and the locations atwhich that advertising content may be sent to a mobile deviceuser, according to one embodiment.FIG. 7 is a flowchart illustrating one embodiment of usingbids for advertising content to determine which location to 40advertise when sending advertising content to a mobiledevice user.FIG. 8 is a block diagram illustrating an embodiment of acomputer system, such as traffic pattern analysis system 100,usable to utilize navigational paths and/or user trails for 45directing advertising content to mobile device users, asdescribed herein.While the invention is described herein by way of examplefor several embodiments and illustrative drawings, thoseskilled in the art will recognize that the invention is notlimited to the embodiments or drawings described. It should 50be understood, that the drawings and detailed descriptionthereto are not intended to limit the invention to the particularform disclosed, but on the contrary, the intention is to cover allmodifications, equivalents and alternatives falling within thespirit and scope of the present invention as defined by the 55appended claims. Any headings used herein are for organizationa! purposes only and are not meant to limit the scope ofthe description or the claims. As used herein, the word "may"

A mobile device user's predicted destination may be determined based on the user's recent traffic pattern, current location, and in some embodiments, demographic informationregarding the cell device user. Thus, the system may be con-figured to determine a predicted destination out of severalpotential destinations along the mobile device user's projected traffic path or trail. Additionally, a history of trafficpatterns of both the current mobile device user and othermobile device users may be used, at least in part, to determinea predicted destination for the mobile device user.Navigational path or traffic pattern information regardingmobile device user navigation between and among physicallocations, such as among various stores in a shopping mall,may be analyzed to determine user trails or navigational pathsbetween and among the locations. Such user trails may beused to aid in various types of advertising decisions, such asdirecting electronic advertising or coupons for a predictednext destination of the mobile device user, or to recommendone or more destinations to the user, according to variousembodiments. Mobile device users' traffic patterns, such asthe order in which users navigate among stores in a shoppingmall, venders in a flea market or rides in an amusement park,may be collected and may be aggregated over time.For example, in some embodiments, system 100 maydetermine one or more other locations from which userstravel to a particular location. For instance, a location L1 maybe frequently visited from locationL2. Thus, a user trail mays used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must).Similarly, the words "include", "including", and "includes"mean including, but not limited to.

60 be considered to exist from locationL2 toLl. Advertisers and

DETAILED DESCRIPTION OF EMBODIMENTSAs noted above, the movements of mobile device usersmay be detected, recorded, tracked and analyzed in order to

other entities may utilize information regarding such trafficpatterns, or user trails, when making decisions regardingadvertising. For example, analysis of traffic patterns maydetermine that a large number of mobile device users visit65 locationL2 prior to visiting location L1. Thus, advertising forlocation L1 (such as sending an electronic coupon for location L1 to a mobile device or other display device) while


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mobile device users are at or leaving location L2 may increasethe visibility of location L1 and/or allow for targeted advertising, such as for a certain product offered at locationL1. Forexample, by analyzing the recent traffic pattern of a mobiledevice user as she moves through a shopping mall, system100 may determine that the mobile device user has visitedthree of the four major clothing retailers in the mall and thusmay determine that she will likely visit the other clothingretailer next. Thus, in one embodiment, system 100 may sendher an advertisement or coupon for the other clothing retailer 1oor for a specific item at the other clothing retailer. Alternatively, in another embodiment, system 100 may recommendthat the mobile device visit the other clothing retailer. Forinstance, the mobile device user may request a recommendation of a store to visit and system 100 may then recommend 15the other clothing retailer.In another example, analysis of mobile device path and/ortrail information may determine that a high number ofmobiledevice users that visit a particular luxury restaurant also visitother locations related to luxury items, such as a winery 20nearby the restaurant. Thus, the winery may desire to sendcoupons or advertisements for the winery to mobile deviceusers that are currently at (or leaving) the restaurant. In yetanother example embodiment, a mobile device user may bevisiting various tourist sites in and around a particular city and 25system 100 may recommend additional tourist sites to themobile device user. As will be described in more detail subsequently, system 100 may analyze the mobile device user'sprevious movements, such as the locations recently visitedand the order in which those locations were visited to deter- 30mine one or more destinations to suggestor recommend to theuser.

6positional information indicating that a mobile device userhas arrived at, or left, a location for which system 100 isconfigured to track visits by mobile device users. Forexample, in one embodiment, system 100 may be configuredto analyze positional reports of mobile device users movingamong stores in a shopping mall and therefore system 100may only retain and utilize (e.g., for the purposes of trafficpattern analysis and destination prediction) positional reportsindicating that a user has arrived at or left one of he stores. Inother embodiments, however, system 100 may be configuredto retain and utilize positional reports indication how (e.g., bywhat geographic path, trail, or avenue) a mobile device user istraveling between locations.Additionally, the number oflocations previously visited bya mobile device user used by system 100 when determining anext location may vary from embodiment to embodiment. Forexample, in some embodiments, only those locations visitedwithin a certain amount of time may be used to determine anext destination. In other embodiments, system 100 mayanalyze a mobile device user's past movements in order todetermine those locations that may be considered a part of heuser's current path, pattern or trail and use those locations todetermine a next destination. In yet other embodiments, system 100 may be configured to only consider locations withina particular geographic or logical area, such as to only consider the stores within a shopping mall, for example. In stillother embodiments, system 100 may allow the mobile deviceuser to determine when system 100 should start and stoptracking the user's movements and therefore only locationsvisited by the user within that time frame (e.g., between thetime the user initiates and concludes system 100's tracking)may be used to determine a next destination. In other words,a mobile device user may be able to define a 's ession' duringwhich system 100 tracks the user's movements, determines

35 next destinations and possibly sends advertising content tothe user.

While described herein mainly by use of the terms "site","location", or "destination", navigational pattern information, paths, and user trails for mobile device users may refer tovirtually any granularity of positioning information. Forinstance, the term "location" as used herein may, in variousembodiments, refer to a particular GPS position based onlatitude and longitude, a particular shopping mall, sportsarena, a city's business district, a individual vendor or shop in 40a shopping, sporting or entertainment venue, individual aislesor sections of a store, or even individual rooms in conferencefacility. Additionally, a mobile device user's movements,both current and past movements may be referred to herein asthe user's "path", "traffic" or "travel" pattern and may be 45analyzed to determine trails or paths among the locationsvisited. Varying levels or granularity of traffic pattern information, navigational paths, and user trails may also be collected, analyzed, and utilized as part of determining predicteddestinations and/or advertising decisions, as described 50herein. For example, in one embodiment, a navigational pathor user trail may indicate how a mobile device user (or users)visited various shopping, sports, entertainment, or businesslocations.In addition, the frequency at which positional information 55is provided to, or obtained by, system 100 may vary fromembodiment to embodiment. For instance, in some embodiments, system 100 may receive positional informationregarding a mobile device once a second, while in otherembodiments, system 100 may receive the positional infor- 60mation less frequently, such as once every minute or onceevery five minutes. Furthermore, regardless of the frequencyat which positional information is available, system 100 mayfilter out some positional information, such as redundantpositional reports regarding a non-moving mobile device, for 65example. In some embodiments, system 100 may analyze allincoming positional information, but only retain or utilize

Positional information regarding the current location of amobile device user may be obtained in any of various manners, according to various embodiments. For instance, mobiledevices are increasingly required to provide Global Positioning Information, such as to support 911 and other emergencyservices. Thus, mobile device 110 may determine its currentlocation using signals from Global Positioning Satellites 130and transmit its current location to a mobile service provider195, such as via the mobi le device normal wireless communication, such as via a network ofcommunication towers 140,such as mobile, cellular and/or satellite communication towers. Thus, in some embodiments, the location of a mobiledevice user may be tracked via GPS data provided by thedevice itself. In various embodiments, mobile device 110may represent a mobile (e.g., cellular) phone, a GPS navigation device (either handheld or vehicle installed), pager, orgenerally any wireless device, such as a PDA or other handheld computer, that can be tracked positionally and treated asa mobile device for the purposes path-dependent advertising,predicting and/or recommending destinations.Alternatively, the location of a mobile device user may bedetermined by cell-signal triangulation by mobile serviceprovider 195. As radio, wireless and cellular signal triangulation is well understood in the art, the details thereo f will notbe discussed herein. In general, any method of determiningthe location of mobile device user may be used to providemobile device user traffic patterns or trails for analysis asdescribed herein.The mobile service provider 195 may provide a service ofdistributing mobile device user's locations via any of variousmeans, such as via a web-based interface over network 120,


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according to different embodiments. In some embodiments,the mobile device user may have signed up or agreed to havehis/her movements tracked and to have positional information regarding their movement be analyzed and included indata utilized by system 100 to determine traffic patterns, usertrails, and to predict, suggest and/or recommend destinations.For instance, a mobile device user's service contract withmobile service provider 195 may include language givingmobile service provider 195 permission to track the user'smovements and/or to provide positional information regarding the user's movements to third parties, such as to system100 for traffic pattern analysis, path-dependent advertising,predicting and or recommending destinations. A in-vehiclenavigational device may also include (either as installed orvia an update) aggregated navigational trail information andthe navigational device may be configured to analyze thevehicles movement according to the navigational informationto recommend destinations and/or to provide advertising content for destinations, as described herein.

8information indicates that a high number of mobile deviceusers visit location L2 from location L1, system 100 maysuggest locationL2 as a potential destination to mobile deviceusers currently visiting location Ll . Similarly, if user trailinformation analysis indicates that a high number of usersvisit location L3 from location L2, advertising or coupons forlocation L3 may be sent to mobile device users currentlyvisiting location L2. Additionally, in some embodiments, system 100 may determine potential destinations for a mobile

10 device user based on multiple locations visited by the mobiledevice user.Thus, system 100 may utilize user trail analysis to determine the location at which to send advertising content tomobile device users. For example, system 100 may commu-15 nicate advertising content for location L2 to mobile deviceusers currently visiting (or that have recently left) location L1

if user trail analysis indicates that locations L1 and L2 are"near" or "proximate" each other according to user trailanalysis. In other words, two locations may be considered20 near each other if mobile device users visit both locationsdditionally, in some embodiments, a mobile device usermay be able to turn on and off the reporting of positionalinformation as desired and to turn on or off he receipt of any

path-dependent advertising and or recommended destinations. In yet other embodiments, a mobile device user mayallow positional information regarding his/her movements to 25be tracked, provided to third parties and used in traffic patte rnanalysis, path-dependent advertising, predicting and recommending destinations while also opting out of receiving anypath-dependent advertising content, coupons, or recommended destinations.

within a short amount of ime even if he two locations are notnecessarily physically near each other. For example, system100 may determine that a large number of mobile device usersmay drive to a particular restaurant after attending a baseballgame at a particular ballpark. Thus, system 100 may considerthe restaurant "near" or "proximate" the ballpark for thepurposes of raffic pattern or user trail analysis. Additionally,system 100 may send advertising content for the restaurant tomobile device users that are current at or have recent left the

30 ballpark.In some embodiments system 100 may be configured tocommunicate with mobile server provider 195 over network120 to obtain the location of mobile device users. In otherembodiments, mobile service provider 195 may be configured to expose an application programming interface (API) orother protocol for providing positional and location information regarding mobile device users.In some embodiments, system 100 may be configured toobtain (or receive) location information regarding mobiledevice users from different mobile service providers 195.System 100 may be configured to store the location information in trail information 180 for current or future analysis. Forexample, system 100 may be configured to continuouslyreceive and analyze positional information regarding manydifferent mobile device users over the course of days, weeks,months or even years. System 100 may store the individualpositional reports, such as in any suitable database formatand/or alternately may aggregate the positional informationfor multiple mobile device users.Additionally, system 100 and/or traffic analysis engine 150may be configured to analyze positional information regarding the movements of multiple (even numerous or many)mobile device users to determine traffic patterns or user trailsamong various locations and destinations indicated by thepositional information. System 100 may also utilize variousmapping or other geographic information to identify variouslocations of interest. For example, system 100 may maintainaccess to positional and geographic location information thatmay include or be annotated with place names and locationboundaries (such as by using GPS data) and system 100 maycompare such geographic location information against positional information regarding mobile device user's movements to determine locations visited by the mobile deviceuser.According to some embodiments, system 100 may analyzenavigational path information in order to suggest potentialdestinations to mobi le device users. For example, if user trail

While described herein as being perfo rmed mainly by traffic pattern analysis system 100, traffic pattern analysis, pathdependent advertising, determining and recommending destinations, as described herein, may alsobe performedby other

35 systems, such as mobile service provider 195, according tosome embodiments. In other embodiments, portions of thefunctionality described herein to system 100 may be performed on other system, such as mobile service provider 195.In other words, in some embodiments, various portions,

40 action, analysis, etc., described herein as being performed bysystem 100 may be distributed to, or among, other systems.In general, a user trail may be generatedby a mobile deviceuser visiting a number oflocat ions in a particular order. Thetrails of a number of mobile device users may be aggregated,

45 such as over time, and analyzed to determine traffic patternsor aggregated navigational paths. Analysis of such trafficpatterns and user trail information may determine that certainlocations are more popular than others and that a high numberof users visit a particular location from another location or

50 that a high number of users visit a certain set oflocations as agroup. In other words, two sites that are otherwise unrelatedmay both be accessed by a high number of common mobiledevice users.Additionally, according to some embodiments, mobile55 device users may be tracked while driving a nd advertisingcontent may be sent to the users for locations they are likely topass by or visit based on their recent and current traffic patterns. For example, mobile device users may be sent couponsfor stores, businesses or vendors based on predicting the60 mobile device user's likely next destination. For instance,mobile device users whose recent driving pattern indicatesthat they are likely headed to the airport may be sent couponsfor a parking service near the airport. Similarly, mobile deviceusers may be tracked as they move around an airport and65 coupons may be sent for food venders near the users' likelydestination within the airport. In other words, by analyzinghow a person moves through the airport, the system may


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predict the person 's likely destination within the airport (e.g.,which concourse, etc.) and the system may then send couponsto the person's mobile device offering discounts at variousvendors (food, newsstands, souvenir shops, etc.) near theperson' s predicted destination.

10

According to various embodiments, "advertising content"may represent any form of communication to the mobiledevices of tracked users regarding one or more locationslikely (such as based on traffic pattern analysis) to be visitedby the mobile device users. In one embodiment, electroniccoupons or other advertisements may be sent to the mobiledevice of he tracked user. In another embodiment , "advertising content" may include wireless, cellular, text or othermessages recommending (with or without advertising content) particular locations.

likely to pass) to an electronic sign or other public displaydevice recommending the gift shop and including the mobiledevice user's name. Additionally, system 100 may sendadvertising content to both the user's mobile device and oneor more public display systems. For example, in one embodiment, advertising content may be displayed on a public display device while a short textual, graphic, or other messagemay be sent to the user's phone alerting them to the displayedadvertising content on the public display device. In one10 embodiment, system 100 may be configured to communicatewith the user's mobile device to cause the device to beep ormake another audible alert as well as, or instead of, displayinga message alerting the user to the displayed advertising con-

15 tent.In some embodiments, system 100 may be configured to

send advertising content, either for a single location or formultiple locations, to multiple public display systems. Forinstance, in one embodiment, system 100 may send advertis-

In yet other embodiments, advertising content may becommunicated to devices other than the mobile device of atracked user. For instance, in some embodiments, advertisingcontent may be sent to a public display device 170 near atracked user or along a pathway likely to be taken by thetracked user, such as may be based on navigational pathinformation and/or locations recently visited by the trackeduser. Thus, in some embodiments, system 100 may be configured to communicate advertising content, not to the mobiledevice, but to some other advertising content display systemlikely to be viewed by the mobile device user. For instance, akiosk, or other electronic sign, in a mall may include a displaydevice and may be configured to receive and display advertising content. As another example, an electronic billboard orsign along a street, road or highway, such as along a road to aparticular location (e.g., store, vender, restaurant, entertainment venue, sports, venue, tourist venue, etc.) may be configured to receive and display advertising content directed to

20 ing content to each of multiple public display systems in turn,such as to engage a mobile device user multiple times as theytravel toward a next likely destination. Furthermore, eachpublic display system may display a different advertisingcontent as different mobile device users travel past, according

25 to some embodiments. Additionally, in some embodiments,public display systems may be capable of printing physical(e.g., paper) advertising content, such as coupons, and/or mayalso be capable of playing audio messages of either advertising content or to draw the mobile device user' s attention to the30 displayed advertising content.

a particular mobile device user traveling along the road.

In some embodiments, analysis of user trail informationmay indicate that more users visit a first location from asecond location than visit the first location from a third location. For example, more users may visit location L1 fromlocation L2 than visit location L1 from location L3. Thus, theowner oflocationL1 may desire to send advertising for loca-tion L1 to mobile device users at or near location L2. According to one embodiment, system 100 may send advertisingcontent for location L1 to the mobile device users on behalfofthe owner of location Ll . Thus, in some embodiments, current mobile device user traffic pattern information may beused to determine when and where (e.g., when a mobiledevice user is at or near a location) to communicate advertising content for a particular location. In other embodiments,

Thus, system 100 may be configured to determine one or 35more public display devices associated with a path likely to betaken by the mobile device user traveling to the predicteddestination. A public display device that is "associated with apath" may include device located at virtually any locationalong or near the path including a user destination at the start, 40end or along the path. The public display device may beconsidered "associated with a path" when the device islocated at virtually any location viewable from a user traveling along a path or trail between a current location for themobile device user and the predicted destination.Thus, after determining a likely destination for a mobiledevice user, system 100 may also determine that the user mayalso pass by a electronic display device capable of receivingand displaying advertising content, which may be updatedwhenever a tracked mobile device user is likely to pass by. 50Advertising content for the likely destination may then besent to the public display system. As described herein, theadvertising content ma y include an advertisement for a particular location, store, venue, product, service, etc., and mayalso indicate a special price, coupon, or other deal if the 55mobile device user makes a purchase at the advertised loca-

45 the system may send more than one advertisement or couponto a mobile device user in order to provide advertisements foreach of several mostly likely locations to be visited by themobile device user.

tion.

In another embodiment, however, the publisher may sendadvertising content for location L1 to mobile device users ator near location L3 in order to generate more traffic fromlocation L3 to location Ll . Also, an advertiser may pay morefor delivery of advertising content to mobile device users atlocations that are more proximate (e.g., according to trafficpattern trails and not necessarily physical proximity) theadvertised location than for delivery of advertising content tomobile device users at locations that are less proximate theadvertised location. For example, if user trail informationindicates that a majority of mobile device users travel from

60 location L1 to location L2 than travel from location L3 toIn some embodiments, the advertising content, whetherdelivered to the mobile device or to a public display system,may be personalized, such as to include the mobile device

user's name, to aid in gaining the mobile device user's attention to the advertising content. For instance, in one embodiment, a mobile device user may be tracked while attending anamusement park. System 100 may determine that the mobiledevice user is leaving an area of rides and entering an area of 65gift, souvenir and/ or other shopping. In response, sys tem 100may send advertising content for a gift shop (that the user is

location L2, an advertiser may pay more to advertise locationL2 to mobile device users at location L1 than to mobile deviceusers at location L3. In other embodiments, however, anadvertiser may pay more to advertise location L2 to mobiledevice users at location L3 than to mobile device users atlocation Ll . In general, the cost of targeted advertising tomobile device users based on user trail information may vary


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according to, or may be dependent upon, the proximity oflocations vis ited by, or likely to be visited by, a mobile deviceuser.

12

Referring to FIG. 1, network(s) 120 may include any suitable data network or combination of networks configured forcommunicating content requests and content between trafficpattern analysis system 100 and mobile service provider 195.For example, network 120 may include one or more LocalArea Networks (LANs) such as Ethernet networks, as well asWide Area Networks (WANs), Metropolitan Area Networks 10(MANs), or other data or telecommunication networksimplemented over any suitable medium, such as electrical oroptical cable, or via any suitable wireless standard such asIEEE 802.11 ("Wi-Fi"), IEEE 802.16 ("WiMax"), etc. Invarious embodiments, all or a portion of network 120 may 15encompass the network infrastructure commonly referred to

100 may determine that a mobile device user has deviatedfrom traffic patterns indicated in aggregated navigation information. In some embodiments, system 100 may track and/oranalyze a mobile device user's anomalous and/or deviatemovements in order to recognize or determine a new trailbetween locations. In other embodiments, system 100 maydetermine that a mobile device user has deviated from arecognized user trail and may communicate informationregarding the fact that the user has deviated from the recognized trail, such as to aid the user navigationally (e.g., in casethe user has lost their way). For example, system 100 maydetermine that a user has visited several tourist-related locations in a city but has deviated from recognized user trailstraveled by tourists. In response, system 100 may be configured to inform the user that they are no longer followingrecognized traffic patterns and may recommend a next desti-as the Internet. In other embodiments, network 120 may beentirely contained within an enterprise and not directly accessible from the Internet.nation from the recognized user trails. In yet other embodiments, system 100 may inform a mobile device user that hasdeviated from recognized user trails regarding the locations

20 along the user's current line ofmovement, such as to warn atourist about entering a dangerous neighborhood or to warn afestival attendee that they are leaving the festival groundsand/or to lure them back into the festival by displaying a

As noted above, the pattern ofmobile device users' movements may indicate pathsor trails among various locations. Insome embodiments, the traffic pattern and resultant trails ofmany different users may be aggregated over time to determine aggregated pattern or trail information. For example, ifmany different mobile device users travel from one location 25to another, a pattern or trail may be considered to existbetween the two locations. Similarly, if many differentmobile device users travel from the second location to a thirdlocation, the trail may be extended from the first location tothe third location via the second location. Additionally, morethan one traffic pattern or trail may exist between or among a

coupon for a vendor within the festival grounds.In yet other embodiments, system 100 may be configuredto communicate a mobile device user's deviant movements(e.g., movements that deviate from aggregated user trails) topeople and/or entities other than the mobile device user, suchas to venue management personnel. For example, system 100

30 may alert authorities that a mobile device user is moving intoa restricted area. System 100 may also be configured to detectpotentially stolen vehicles, cargo or other goods based ondetermining that a mobile device has deviated from recognized traffic pattern and/or user trails. In general, determiningset oflocations. For instance, using the same three locationsmentioned above, one trail may exists from the first locationto the second location and on to the third location, whileanother trail may exist from the first location to the thirdlocation without passing through the second location, indicating that some mobile device users travel from the firstlocation to the third location without visiting the second location.When analyzing a mobile device user's traffic pattern, thesystem may record, such as in trail information 180, theidentification of the person 's current location as well as anyother locations that the person has visited within a fixedamount of ime (e. g., in the last hour). In some embodiments,service provider 195 may supply positional information tosystem 100 for analysis. In other embodiments, however,service provider 195 may perform some or all of the trafficpattern analysis described herein. System 100 may store positional and location information in any of various forms. System 100 may analyze positional information regarding anumber of mobile device users in order to identifY or determine patterns, paths and/or trails among various locationsvisited by mobile device users. For example, by determininglocations visited by various mobile device users and the orderin which those locations were visited, system 100 may identifY one or more patterns between and/or among those locations. The identified trail, pattern or path information may beused or taken into account when analyzing another mobiledevice user's movements among the same locations. Moreover, system 100 may be configured to compare one mobi ledevice's movements to patterns, paths and trail identifiedfrom analysis of other mobile device's movements, such as todetermine a likely next destination.Additionally, system 100 may be configured to analyze amobile device's movement in order to recognize anomalousmovements or movements that deviate from recognized userpaths, according to some embodiments. For example, system

35 whether and whe n mobile device users deviate from recognized user trails may indicate an "interest anomaly" to befurther tracked and analyzed. For example, over time, system100 may determine and maintain information on "deviant"trails and recognize when a mobile device user travels along

40 a deviant trail.System 100 may also create a weighted link between thevarious locations visited by the mobile device user, in someembodiments. Additionally, the current mobile device user'spath or trail may be compared to other user's paths to deter-45 mine a next most likely destination. For example, the number

of traversals between two locations may be recorded andmaintained. In other words, if a current mobile device userhas visited locations A, B, and C and sys tem 100 determinesthat a majority of the mobile device users that visit locations50 A, B and C also visit location D, the system may send advertising content for location D to mobile device users currentlyat locations A, B and/or C.Furthermore, different trails, patterns or paths may be identified as being used by different types of mobile device users.55 For example, different age groups ofmobile device users mayuse different patterns or trails among locations. Similarly,different demographic information may be utilizedby system

100 to identifY various groups ofmobile device users and thepaths or trails used by those respective groups when moving60 among locations. In other words, demographic informationregarding a mobile device user may be used, at least in part,when determining a next likely destination for the mobiledevice user. Additionally, information regarding previouspurchases may also be used, as least in part, when determin-65 ing a next likely destination or when determining particularadvertising content to send to a mobile device user, accordingto various embodiments.


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System 100 may be configured to use any of various analy-sis methods when analyzing positional information to determine patterns, trails, predicted destinations, etc., according todifferent embodiments. For example, in one embodiment,system 100 may divide the number of traversals by mobiledevice users from A to B by the total numbe r of traversals tolocation B and use the result as the probability of anothermobile device use r traversing from location A to location B.System 100 may also determine the probability of traversingfrom location A to other locations as well. When a mobiledevice user is at or leaving location A, the system may sendadvertising content, such as coupons, based on the locationthat has the highest probability of be visited from location A,according to some embodiments.In some embodiments, different locations that are accessedby mobile device users in close proximity to another locationmay be considered near or proximate the other location. Forexample, when navigational pattern information indicatesthat mobile device users travel from a first location to a secondlocation and then on to a third location, the three locationsmay be considered "near" or "proximate" each other. In oneembodiment, the first location may be considered nearer, ormore proximate, the second location than the third locationand the third location may be considered nearer, or moreproximate, the second location than the first location. As usedherein a location may be considered near or proximateanother location based on the fact that mobile device usersvisit the two locations within a certain amount of time orwithout visiting other locations and may not be related to theactual physical proximity of the two locations. For example,in one embodiment system 100 may be configured to trackmobile device users' movements among stores in a shoppingmall and only the stores in the mall may be considered locations or destinations for traffic pattern analysis. In someembodiments, system 100 may only consider a mobile deviceuser to have visited a location (e.g., a store in this example)when the mobile device user is actually inside the store andnot merely walking by the store. As mobile device users visitdifferent stores, system 100 may determine various trafficpatterns or user trails among the stores. For example, somemobile device user may only visit clothing retailers whileother mobile device users may only visit music stores. Inother embodiments, other criteria may be utilized to determine when a mobile device user is actually visiting a location.Path-dependent advertising content may be delivered automatically by system 100 whenever the system determines alikely future destination for a mobile device user. Additionally, in other embodiments, the mobile device user mayrequest a coupon for a particular store or may request arecommendation of one or more destinations. A mobiledevice user may have signed up for a service in which coupons and other advertising are offered via their mobile device

14local or from out-of-town may be determined and differentnavigational path information may be used when predictingpotential destinations. For instance, tourists may travel alongdifferent paths or trails than those used by local mobile deviceusers and the system may be configured to maintain andutilized different sets of aggregated navigational informationaccording to whether a mobile device user is local or fromout-of-town, according to one exemplary embodiment. Similarly, the system may supply tourist related information, such

1o as recommended destinations visited by other tourists or maysupply local information to tourists, in various embodiments.The system may record demographic information regarding mobile device users along with the other informationregarding mobile device traffic patterns. For instance, when15 determining a next predicted destination from location A,younger mobile device users may be most likely to visitlocation B from location A, whereas older mobile device user

may be more likely to visit location C from location A. Thus,information other than just the mobile device user's recent20 locations and traffic patterns may be used when determininga next destination.Coupons or other advertising content may be for particular

products or service or may be more generally directed to thestore, vendor, or location. Demographic information regard-25 ing a mobile device user may be used to determine one ormore particular products to feature in the advertisement orcoupon. Coupons may be provided for products that have not

be previously purchased by the mobile device user but whichthe user is likely to purchase according to "traditional market-30 based analysis" of the user's purchases. For instance, system

100 may be configured to analyze information regardingrecent purchases by a mobile device user when determining anext likely destination and may also take a user's recentpurchases into account when determining or selecting the35 advertising content to communicate to the user. For example,

if system 100 determines that a mobile device user just purchased a very expensive dress, system 100 may send advertising content, such as to the user's mobile device or to apublic display system, recommending and/or advertising

40 either a high-end shore store and/or a high-end accessoryboutique.In other embodiments, system 100 may be configured totrack mobile device users as they move around withi n a store,such as a grocery or department store, and to determine a next

45 or predicted destination within the store based on the user'scurrent and recent path information through the store. System100 may then communicate advertising content to the user(e.g., to the user's mobile device or to a public display device)advertising or recommending the predicted destination

50 within the store. System 100 may also include advertisingcontent (or a coupon) for one or more specific products basedon the areas of the store already visited by the mobile deviceuser. For instance, in one embodiment, system 100 may tracka mobile device user around a store and determine that theor via one or more public display devices. Whe n the personvisits a store, he can either have a coupon automaticallyprovided or suggested to him or he may request a coupon 55(either for his current location or for a recommended futuredestination).user is likely to visit the dairy section next and may deliveryadvertising content for one or more dairy products to themobile device user. As described above, system 100 maycommunicate the advertising content to the user's mobiledevice or to a public display device within the store, or both.For example, system 100 may communicate the advertisingcontent to a coupon-printing device that the mobile deviceuser is likely to pass on the way to the dairy section. System100 may also alert the use r to the advertising content, such asby causing the mobile device to play an audio alert (e.g., a

In some embodiments, other demographic informationregarding the mobile device user may also be analyzed andused to predict a most likely destination. For instance, the 60identity of the mobile device user may be known and therefore demographic segmentation that might drive purchasingbehavior may be taken into account when predicting a predicted next destination for the mobile device user. Forexample, the age of he mobile device user may be taken intoaccount when determining a next predicted destination. Insome embodiments, wheth er or not the mobile device use r is65 beep or special ring tone) or to display a message alerting theuser to the displayed advertising content. Additional information, such as the mobile device user's purchasing history,


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aggregated path information for other users may also be usedby system 100 when determining a next location for themobile device user and when determining the particularadvertising content to display to the user.

In some embodiments, system 100 may be able to obtain orreceive demographic information including informationregarding mobile device users' previous purchases via athird-party system. In other embodiments, however, system100 may be configured to receive recent purchase informationregarding a mobile device user from an integrated purchasing 10system at the locations visited by the mobile device user. Inyet other embodiments, the mobile device may also be integrated with a purchasing system, such as to allow a user of hemobile device to make purchases using, for example, an elec- 15tronic purchasing or commerce system executing on themobile device.

16considered to be more proximate to a particular location thana site visited by users by lower quality.A user's level of quality may be different for differentlocations or destinations, according to different embodiments. For example, one user may be considered high qualityfor one type of store, such as a jewelry store, but may beconsidered low quality for another type of store, such as ateen-oriented music store. Similarly, a user may be consid-ered of high quality for the music and oflower quality for thejewelry store. Additionally, a user's level of quality may bedifferent for different stores of he same type. For example, auser may be considered of high quality for a less expensivejewelry store but considered oflower quality for a store selling higher-end, custom jewelry. Thus, system 100 may notdetermine or maintain a single measurement of quality for anindividual mobile device user. Instead, system 100 may beconfigured to determine a measure of quality for a user basedon individual (or particular types of) destinations. In otherwords, a user's level of quality may vary based on the par-

In some embodiments, a small software or firmware program may be installed on the mobile devices to report GPSinformation. In other embodiments however, the system mayreceive location information regarding mobile device usersfrom mobile device service provides. I fa software program isinstalled on the mobile device, the system may be configured

20 ticular destination or location for which the user's level ofquality is being determined.In some embodiments, system 100 may be configured to

only send coupons or advertisements for a particular locationto mobile device users of a certain level of quality. Foro send more detailed advertising and/or coupons. The coupons may be delivered to the mobile device in a number ofmanners, such as via a mobile device call, an email messageto the mobile device, a text message to the mobile device, etc.25 example, a high-end jewelry store in a shopping mall mayonly desire to advertise to mobile device users of a certainlevel of quality. Thus, various factors and/or criteria may beused to determine which locations to advertise to whicharious criteria may be used to determine whether onelocation is proximate another location or to determinewhether one location is more proximate than another location 30to a third location, according to different embodiments. Inanother words, a level of proximity may be determined forvarious locations in relation to a particular location. Forexample, in one embodiment, the number oflocat ions visited

by mobile device users between two other locations may be 35used a measure ofwhether one location is proximate another.Thus, a given number of hops taken by mobile device usersbetween two locations may determine whether the two locations are proximate. Additionally, the number of hopsbetween two locations may correspond to a level of proximity 40between the two locations. In another embodiment, the number of mobile device users that travel a particular path or trailor the number of users that visit two locations, whether or notevery mobile device user follows the same path between thelocations, may determine whether the two locations are pro xi- 45mate. In yet another embodiment, the amount of timebetween when mobile device users access two locations maybe used as a criterion to determine how proximate the twolocations are.Additionally, mobile device user quality, or aggregate user 50quality, may be used to determine the proximity oflocations.As noted above, demographic information based on the identity of mobile device users may be available in some embodiments and may be used to determine a level of user quality. Alevel of quality may indicate the likelihood that an individual 55user may purchase particular types of tems or visit particulartypes of locations. For instance, the average or aggregatequality of all users that visit two locations may be used todetermine whether the two locations are proximate. Thosemobile device users determined to be more likely to make a 60purchase may be considered ofhigherquality for determiningthe proximity of wo locations visited by those mobile deviceusers. Similarly, information regarding other locations visitedby users, users' occupation, household income level, recentpurchases, etc. may be used, at least in part, to determine a 65mobile device user's level of quality. Thus, a location visitedby mobile device users of higher average quality may be

mobile device users. In the jewelry store example above, thejewelry store may also desire to advertise to mobile deviceusers that are currently visiting (or recently left) anotherjewelry store in the same shopping mall. Similarly, while anaverage car rental company may desire to advertise to anyand/or all mobile device users waiting an the baggage terminal of an airport, a high-end limousine company may onlydesire to advertise to mobi le device users of a certain level ofquality or that also visited the airports executive (e.g., firstclass or business class) lounge.Additionally, when more than one trail or path existsamong various locations, the different tails may be weightedaccording to various techniques. For example, in one embodiment, the amount of actual traffic, e.g. the number of mobiledevice users, traveling along a particular path may be used toweight different user trails. Thus, a trail which more userstravel may be weighted more heavily that a trail that fewerusers travel, according to one embodiment. In anotherembodiment, more recently traveled trails may be weightedmore heavily that trails that have not been traveled as recently.Additionally, the weighting of trails or individual links orhops along trails traveled by mobile device users betweenlocations may be used, at least in part, when determining apossible or predicted next destination for a mobile deviceuser. Thus, sys tem 100 may be configured to take into accountthe weighting of ndividual links for hops along user trails andthe weighting of complete trails between locations whendetermine a next likely destination for a mobile device user.Additionally, since a mobile device users' likely or predicteddestination may be used to determine what advertisement orcoupons to send to the user's mobile device, the weighting ofuser trails may, at least in part, determine what coupon oradvertisement may be displayed to the user (e.g., on the user'smobile device and/or displayed on one or more public displaydevices).As described above, system 100 may receive positioninformation regarding a mobile device user from custom orspecialized software running on the user's mobile device. Forexample, as illustrated in FIG. 1, mobile device 110 may


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include positioning reporting logic 160 configured to reportthe mobile device position (such as according to GPS information) to system 100, either directly or via the user's mobileservice provider 195. For example, in one embodiment, position reporting logic 160 may represent custom software orfirmware configured to capture and/or report a mobile deviceuser's navigational activity.

18computerized bidding systems are well understood in the art,the details of such a system will no t be discussed herein.Additionally, the cost charged for delivering advertisingcontent to mobile device users may be based on navigationalpattern or user trail information, according to some embodiments. For example, the highest rates may be charged fordisplay of advertising to mobile device users who are on orassociated with more popular user trails (e.g., trails that havehigher traffic volume). In some embodiments, the cost of

10 delivering advertising content to a mobile device user mayvary depending upon how proximate the advertised locationis to the location of the mobile device user when the advertising content is displayed.

In some embodiments, position reporting logic 160 may beconfigured as a self-contained, platform-independent software module that may be downloaded, remotely invoked orotherwise obtained from a third party (e.g., the party providing traffic pattern analysis sys tem 1 00) and implemented withminimal alteration to the configuration of mobile device 110.Upon activation, position reporting logic 160 may be configured to report the mobile device's current location and/or 15recent posit ion history (e.g., more than one location) to trafficpattern analysis system 100 in a marmer that is generallytransparent to the other operations performed by mobiledevice 110.

In some embodiments, a mobile device user may request acoupon or advertisement for a location proximate to the user'scurrent location. For instance, a mobile device user visitingvarious vendors at a flea market may request a recommendation of other locations or vendors to visit and, in response,system 100 may determine a new location (which the mobileTraffic pattern analysis system 100 may, in some embodiments, be configured to store received traffic pattern and usertrail data using any suitable format or methodology. Forexample, traffic pattern analysis system 100 may store suchdata in arrays, tables, trees, databases, hashed structures orother suitable data structures, either internal to traffic patternanalysis system 100, such as in trail information 180, ordistributed among one or several external systems (notshown) such as database systems, file systems, etc. In someembodiments, traffic pattern analysis system 100 may storehistorical content request traffic data for arbitrary periods oftime, while in other embodiments data older than a thresholdage (e.g., days, months, etc.) may be automatically purged ormoved to secondary storage.

20 device user has not visited recently, for example) based on theuser's currently location and, in some embodiments, based onthe locations the mobile device user has recently visited. Inother words, the locations recently visited by a mobile deviceuser prior to visiting the user's current location may effector

25 change the location or locations recommended, according tosome embodiments.Additionally, when recommending locations or destinations to a mobile device user, system 100 may also take intoaccount previously determined user trails among the loca-

Generally speaking, recording information regarding thenavigational path taken by a mobile device user to a particularlocation may be conceptually similar to an insect marking itspath with a pheromone. I f a sufficient number of users travel

30 tions proximate to the mobile deviceuser's current and recentlocations. For example, system 100 may recommend a location to a mobile device user based on aggregated traffic pattern of other mobile device users. In some embodiments,additional demographic information about the mobile device35 user may be used to select a particular destination to recommend. Thus, system 100 may recommend one or more destinations visited by other mobile device users that fall into the

same or similar demographic segments as the requestingmobile device user.to a particular location through a certain set of paths, thosepaths may be distinguished from other paths (e.g., randompaths) via the accumulation of "pheromone" (e.g., recorded 40traffic information). It is noted, however, that the use of theterm "pheromone" in this context is purely illustrative ormetaphorical and that some characteristics of biologicalpheromones may not be directly applicable to analysis ofcontent request traffic as described herein.

A sequence of paths in which the destination of one pathfunctions as the origin of another path may be referred to as anavigational pattern or user trail. A collection of locations ordestinations may present a variety of navigation paths anduser trails along which a mobile device user travels from one45 location to another. Relationships or user trails among locations may be represented as a network or graph, ofwhich oneembodiment is illustrated in FIG. 2.Additionally, mobile device users ' traffic patterns and usertrails may be analyzed in various manners according to different embodiments. For example, U.S. patent applicationSer. No. 11/321,890, tit led Method and System for Determining Interest Level of Online Content Navigational Paths, filed 50Dec. 29, 2005, which is hereby incorporated by reference inits entirety, describes various ways and manners of analyzingnetwork users trail information as online users access variousnetwork resources, such as web sites, online databases, etc.,and such ways and marmers may be applied to mobile device 55trails and travel patterns.As noted above, advertisers, such as store owners, vendors,etc., may desire to bid on delivering advertising to mobiledevice users, such as to have an advertisement for a particularlocation (e.g., store, restaurant, kiosk, etc.) be displayed to 60mobile device users when the advertised location is deter-

In the illustrated embodiment, navigational pattern information 200 is shown to include a number of locations (e.g.stores, vendors, kiosks, entertaiument venues, restaurants,etc.) 21Oa-k. Locations 210 may encompass, for example, anyof he various types or configurations oflocations or destinations discussed previously. Paths relating different locations210 are shown as directional arrows between the related loca-tions. Thus, for example, paths exist between location 210aand locations 210b-d. By contrast, no direct path existsbetween location 210a and locations 210e, although a mobiledevice user might travel between these locations via location210c. In some instances, where one path exists from a firstlocation 210 to a second location 210, other paths may alsoexist that lead from the second location 210 back to the firstlocation 210, either directly or via some other location 210.Consequently, it is possible that cycles may exist within navigational pattern information 200, although for simplicity of

mined, such as by system 100, to be a predicted next destination for the mobile device user. Thus, in some embodiments,system 100 may communicate with one or more other compute r systems (not shown) to facilitate automated bidding forplacingof coupons or advertising content on mobile device ofusers likely to visit the advertised location. As automated and65 exposition these are not shown in the illustrated embodiment.

It is noted that navigational pattern information 200 mayrepresent relationships between locations 210 at the level of


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mobile device user travel. The paths shown in navigationalpattern information 200 may or may not correspond to physical paths, roads, or other directly physical connections amongthe locations. For example, two locations 210 may be adjacent in navigational pattern information 200 if a mobiledevice user navigates from one to the other.

20location 210b in decreasing order, such that location 210/ranks highest followed by locations 210c and 210e. Thus,when determining predicted next destinations for mobiledevice users from location 210b, location 210fmay be advertised or suggested prior to or given more weight than, or beassociated with higher priced advertising than, locations 21Ocor 210e. Similarly, location 210b may be considered near orproximate locations 210a, 210c, 210e, 210f and210g, according to one embodiment. Therefore, in one embodiment, path

In some embodiments, navigational pattern information200 may represent the order in which mobile device usersvisited various locations and not the actual physical pathstaken between those locations. For instance, in a shoppingmall, mobile device users may visit a store at location 210aand then walk to the other end of the shopping mall to visit astore at location 210b. If the mobile device user did not visitany other stores on the way, navigational pattern information200 may represent a single hop between the two stores eventhrough the mobile device user may have walked past manyother stores along the way. In other embodiments, however,navigational pattern information 200 may record and takeinto account the locations a mobile device user may passwhen traveling between two locations. Additionally, system100 may send coupons or advertisements to a mobile deviceuser (either directly to the mobile device or to a public displaysystem) for stores or other locations that the user may passwhile traveling to a next destination. For example, system 100may have recommended that the user visit a particular location and may also send advertisements for locations along thepath the user is likely to take to arrive at the recommendedlocation.

10 weights may be used to rank the paths from location 210a indecreasing order, such that location 210b ranks highest followed by locations 210d and 210c. Thus, when determiningpredicted next destinations to advertise or recommend tomobile device users at location 210a, location 210b may be15 advertised or suggested before locations 210c or 210d.As noted above, the placement of advertising content (e.g.,where the mobile device user is when advertising is sent) mayalso be determined based on navigational paths or user trails.Thus, in some embodiments, an advertisement for location20 210b may be sent to mobile device users at or near one ormore of he locations near 21Ob, such as locations 21Oa, 21Oc,210e, 210/and/or 210g. For ease of discussion, the above

examples only locations that are directly adjacent (withinnavigational pattern information 200) to a particular location25 are indicated as near that location. In other words, in the aboveexample, a location is proximate another location if navigational pattern or user trail information indicates that mobiledevice users travel from one of the locations to the otherlocation. In the above example, two locations may be considered near or proximate each other regardless of whethermobile device users travel from one location to the other orvice versa. In other words, location 210b may be considerednear location 210/ and 210c, according to some embodiments. However, advertising for location 210b may not besent to mobile device users at location 210/ if navigationpattern information 200 indicates that mobile device users arelikely to move from location 21Ob to location 21Ofand not the

other way. In other embodiments, however, other metrics orrelationships between locations may be utilized to determinea location 's proximity to another location. For example, locations within a specified number of links or hops within navi-gational pattern information 200 may be considered near eachother (regardless of he locations' actual physical proximity).For example, in one embodiment, locations that are within

Conversely, locations that are close in terms of physicalgeography may be distant in terms of the navigation path 30topology of navigational pattern information 200. Forexample, even though two locations may be physically adjacent, few if any mobile device users may travel directly fromone of he locations to the other. Thus, in some embodiments,the navigation path topology represented by navigational pat- 35tern information 200 may differ or diverge from the physicalgeography of the locations included in navigational patterninformation 200. Since, in some embodiments, the user trailsindicated by navigational pattern information 200 may beidentified through an analysis of actual mobile device users' 40movements, the representation of navigational pattern information 200 may not represent every possible navigation paththat exists among locations 210. Rather, it may represent onlythose paths for which an actual traversal by a mobile deviceuser has been reported.As mentioned above, numerous navigational paths or usertrails may exist within navigational pattern information 200.However, different paths may vary, sometimes substantially,with respect to various measures of path usage. In someembodiments, a representation of navigational pattern infor- 50mation 200 may include indications of weights along thepaths between locations 210, where the weights may reflectany suitable measure of usage or activity of he correspondingpath. For example, paths between certain locations may betraversed by a high volume of mobile device users relative to 55paths between other locations. In one embodiment, a measure

45 two link or "hops" may be considered near each other. Thus,in such an example, locations 210b, 210c, 210d, 210e, 210/,210i and 21 OJ may all be considered near location 21Oa, sincethey are all within two hops oflocation 210a.

of navigation volume of a path, such as a number of pathtraversals pe r unit of ime, may be assigned as a weight of hatpath. Alternatively, some paths through navigational patterninformation 200 may exhibit a substantial rate of change 60relative to other paths. Correspondingly, in one embodimenta time rate of change of the number of traversals of a givenpath may be assigned as a weight of that path.For a given location 210, path weight information may beused in generating advertising or destination recommenda- 65tions from the set oflocations near the given location 210. Forexample, path weights may be used to rank the paths from

Additionally, as described above, other metrics or techniques other than the number of hops between locations,indicated by navigational pattern information, may used todetermine whether two locations are proximate each otherand therefore possible destinations from each other. Forexample, in one embodiment, if one or more mobile deviceusers visit two locations within a specified period of time thetwo locations may be considered near each other. Similarly,user quality, such as based on demographic information and/or the identity of the mobile device user, and other criteriamay be used to determine a level of proximity between twolocations. Additionally, as noted above, advertising contentmay also be sent to public display systems rather than, or inaddition to, sending advertising content to the user's mobiledevice.FIG. 3 is a flowchart illustrating one embodiment of amethod for delivering advertising content to a mobile devicefor a predicted next destination for mobile device user. Asillustrated by block 300, system 100 may be configured to


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US 8,073,460 Bl21

determine one or more predicted destinations for a mobiledevice user based on one or more locations visited by themobile device user. For example, as described above, system100 may receive positional information, such as GPS information, regarding a mobile device user and may determine alocation or destination likely to be visited by the mobiledevice user. As noted above, system 100 may determine apredicted next destination for a mobile device user automatically in some embodiments.In other embodiments, however, system 100 may deter- 10mine a predicted destination for a mobile device user inresponse to a request from the mobile device user. Forinstance, a mobile device user may request a recommendationas to a destination. For example, custom software or firmware

22criteria used to determine whether two locations are within agiven proximity may also be used to rank various locationsaccording to how near or proximate they are to a particularlocation.

In some embodiments, system 100 may be configured toonly consider locations within a given proximity to a mobiledevice user's current location when determining potential orpredicted destinations for the user. For example, in oneembodiment, system 100 may only consider locations withina single link or hop of a mobile device user's current locationin the network traffic information when determining a pre-dicted next destination for the user. In other embodiments,however, system 100 may be configured to consider any location along a mobile device user's current trail or path whendetermining predicted next destinations.Additionally, the quality of he users visiting locations maybe used both to determine whether one location is within agiven proximity of another location and/or to rank the relativeproximity of various locations. For instance, user profile

on the mobile device may enable the mobile device user to 15send a request to system 100, either directly or via mobileservice provider 195, for a recommended destination. Insome embodiments, a mobile device user ma y also be able torequest a coupon and/or a recommended destination fromsystem 100. 20 information, demographic information or characteristics ofother locations visited by similar (e.g., in terms of demographic segment or user profile) mobile device users may beused to determine or rank the quality of mobile device usersvisiting locations. In one embodiment, a location may be

In yet other embodiments, system 100 may track mobiledevice users movements and only when a mobile deviceuser's recent traffic patterns indicate that the user is travelingalone certain traffic paths or user trails will system 100 determine a predicted next destination for the mobile user. 25 considered proximate a particular location if the quality ofmobile device users that visit the particular location from theother location meet a certain criteria. For example, if he usersalso visited a number oflocations related to luxury items or if

When determining a likely destination for a mobile deviceuser, system 100 may select a predicted destination based onthe user 's current location, such as selecting a store physicallyadjacent to or near the mobile device user's currently location, according to one embodiment. In other embodiments, 30however, system 100 may be configured to analyze the current user's recent movements in relation to historical oraggregated traffic patterns of other mobile device usersamong the same locations. Thus, system 100 may analyzenavigational pattern information, such as navigational pattern 35information 200, to determine one or more locations likely tobe visited by the mobile device user. In general, any of methods and techniques described above regarding analyzing traf-fic patterns may be utilized by system 100 to determine alikely destination for a mobile device user.

they recently made a number of purchases, those users may beranked higher in quality than other users. Thus, the quality ofusers that visit a particular location via certain network pathsor that also visit other proximate locations may be used, atleast in part, to determine the proximity oflocations as well asto determine a predicted next destination for mobile deviceusers.After determining one or more predicted destinations forthe mobile device user, system 100 may be configured todetermine advertising content associated with the predicteddestinations, as indicated by block 320. For example, in one

40 embodiment, system 100 may select one particular electroniccoupon from among various available coupons to send to themobile device user. For instance, system 100 may analyzeadditional information regarding the mobile device user, suchAs desc

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