1. Field
The subject matter disclosed herein relates to data processing, and more particularly to methods and apparatuses that utilize one or more premium rules to associate a premium markup to a base bid for online advertising.
2. Information
Data processing tools and techniques continue to improve. Information in the form of data is continually being generated or otherwise identified, collected, stored, shared, and analyzed. Databases and other like data repositories are common place, as are related communication networks and computing resources that provide access to such information.
The Internet is ubiquitous; the World Wide Web provided by the Internet continues to grow with new information seemingly being added every second. With so much information being available, advertising on the Internet often allows advertisers to target audiences viewing their advertisements. Use of the Internet for online advertising facilitates a two way flow of information between end users and advertisers. For example, an end user may request an ad and in doing so may provide information in the form of data that describes the end user in some manner. Conversely, traditional print and “hard copy” advertising may constitute a one-way flow of information from advertisers to end users.
Claimed subject matter is particularly pointed out and distinctly claimed in the concluding portion of the specification. However, both as to organization and/or method of operation, together with objects, features, and/or advantages thereof, it may best be understood by reference to the following detailed description when read with the accompanying drawings in which:
Reference is made in the following detailed description to the accompanying drawings, which form a part hereof, wherein like numerals may designate like parts throughout to indicate corresponding or analogous elements. It will be appreciated that for simplicity and/or clarity of illustration, elements illustrated in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements for clarity. Further, it is to be understood that other embodiments may be utilized and structural and/or logical changes may be made without departing from the scope of claimed subject matter. It should also be noted that directions and references, for example, up, down, top, bottom, and so on, may be used to facilitate the discussion of the drawings and are not intended to restrict the application of claimed subject matter. Therefore, the following detailed description is not to be taken in a limiting sense and the scope of claimed subject matter defined by the appended claims and their equivalents.
In the following detailed description, numerous specific details are set forth to provide a thorough understanding of claimed subject matter. However, it will be understood by those skilled in the art that claimed subject matter may be practiced without these specific details. In other instances, well-known methods, procedures, components and/or circuits have not been described in detail.
Some exemplary methods and systems are described herein that may be used to determine premium bidding of online advertisements. As used herein the phrase “online advertisements,” “advertising,” and/or the like may refer to pop-up ads, banner ads, and/or the like. Such online advertisements may be described below as an ad unit. Such an ad unit may include a keyword term and a creative component. For example, such an ad unit may include text, graphic or video data (herein referred to as “creative component”). Additionally, metadata associated with a banner ad (and/or other like creative components) may include one or more keyword terms associated with the ad unit. Such ad units may be delivered to an end user based at least in part on one or more forms of online marketing processes, such as on contextual advertising, search advertising, search engine marketing, sponsored listings, and/or the like, and/or combinations thereof, for example. As will be described in greater detail below, certain exemplary embodiments described herein may provide mechanisms for advertisers (and/or other like entities) to control how certain ads may be targeted online to publishers, pages and/or end users. Similarly, certain exemplary embodiments described herein may provide mechanisms for advertisers to control additional premium markups associated with a targeting of certain publishers, pages and/or end users.
Such methods and systems that may be used to determine premium bidding of online advertisements, as described herein, may be utilized to provide a flexible and structured mechanism for advertisers (and/or other like entities) to control premium markups associated with a targeting of certain publishers, pages and/or end users. For example, such methods and system may allow for a flexible and extensive taxonomy for target dimensions to include various combinations of the following: an end user demographic, end user location, time, end user interests, publication content, publication Uniform Resource Locator (URL), publication domain, publication site, and/or the like, and/or combinations thereof. For example, in some embodiments, premium rules may be formed as decision trees associated with a single target dimension (referred to herein as basic premium rules) and/or as decision trees associated with two or more target dimensions (referred to herein as composite premium rules). Additionally, such methods and system may provide a conflict resolution between various premium rules. For example, a group of two or more premium rules may be forbidden from reusing identical target dimension sets. Further, a hierarchical target node structure may include one or more target nodes associated with a first target dimension and one or more nodes associated with a second target dimension. In such a case, such a first and second target dimensions may be restrained so that a comparison of a current context to such two or more target dimensions may match no more than one target node associated with a first target dimension and no more than one target node associated with a second target dimension.
Referring to
Process 100 depicted in
During typical online activity, an end user 110 may request a page and/or other like data file(s) of content from publisher device 108, as illustrated at action 112. Publisher device 108 may, in turn, return a content page to the end user, where the content page may contain a link and/or the like to a request for an advertisement from ad manager 106, as illustrated at action 114. In the illustrated embodiment, ad server 112 handles requests for advertisements from end users 110, as illustrated at action 116. Such a request for advertisement may include an HTTP request for advertising content initiated by a content page provided by publisher devices 108 to end users 110. For example, a request for advertisements may contain one or more current contexts associated with a given end user including a taxonomy of user centric data and/or publisher centric data. Such user centric data may include or otherwise be associated with an end user demographic (e.g. age, gender, income, and/or the like), end user location (e.g. continent, country, state/providence, city, zip, and/or the like), time (e.g. end user time, advertiser time, coordinated universal time (UTC), and/or the like), end user interests (e.g. sports, politics, and/or the like), and/or the like, and/or combinations thereof. Such user publisher centric data may include or otherwise be associated with publication content (e.g. shopping, search, and/or the like), publication Uniform Resource Locator (URL), publication domain, publication site, and/or the like, and/or combinations thereof. For example, a request for advertisement may specify a current context including end user gender, such as male or female, and/or the like. Similarly, a request for advertisement may specify a current context including end user age, such as age in years, by birthday, and/or the like, for example. Likewise, a request for advertisement may specify a current context including end user location, such as a geographic location, address, latitude and longitude, Global Positioning System location, and/or the like, for example. Further, a request for advertisement may specify a current context including end user time, such as a time of day, time zone, and/or the like, for example. Similarly, a request for advertisement may specify a current context including coordinated universal time (UTC), such as Greenwich Mean Time (GMT), other non-location dependent time measures, and/or the like, for example. Likewise, a request for advertisement may specify a current context including publication content, such as topic areas associated with such content, key words associated with such content and/or the like, for example. Further, a request for advertisement may specify a current context including publication URL, publication domain, and/or publication site that may refer to all or a portion of a string of characters used to represent a resource available on the Internet, for example. For example, a request for advertisement may specify that the requesting content page is directed towards “sports”, located on the domain “example.com”, that the end user is a male between the ages 18 and 25, that the end user is located in California, and that the end user device's screen resolution is 800 by 600 pixels.
As used herein, the term “content page” may include any information in a digital format, of which at least a portion may be perceived in some manner (e.g., visually, audibly) by a end user if reproduced by a digital device, such as, for example, a computing platform. For one or more embodiments, a content page may comprise a web page coded in a markup language, such as, for example, HTML (hypertext markup language), and/or the like. However, the scope of claimed subject matter is not limited in this respect. Also, for one or more embodiments, the content page may comprise one or more elements. The elements in one or more embodiments may comprise text, for example, as may be displayed as part of a web page presentation. Also, for one or more embodiments, the elements may comprise a graphical object, such as, for example, a digital image. Unless specifically stated, a content page may refer to either the source code for a particular web page or the web page itself. Each web page may contain embedded references to images, audio, video, other web documents, etc. One common type of reference used to identify and locate resources on the web is a Uniform Resource Locator (URL).
In the illustrated embodiment, ad manager 106 may be operative to receive advertising data associated with one or more advertisers, as illustrated at action 118. In one embodiment, advertising data may comprise text, graphic or video data (herein referred to as “creative component”) related to a given ad unit. Such an ad unit may include a keyword term and a creative component. For example, ad manager 106 may receive metadata associated with a banner ad or other like ad including, but not limited to, one or more keyword terms associated with the ad unit. In addition, advertising data also may comprise one or more rules associated with a given ad unit. As will be described in greater detail below, such rules may formed as, or be used to form, a premium rule including one or more constraints or rules that may determine the cost of such advertising based on a determination of one or more target dimensions. By way of example but not limitation, such target dimensions may be associated with and/or include a taxonomy of user centric data and/or publisher centric data. Such user centric data may include or otherwise be associated with an end user demographic (e.g. age, gender, income, and/or the like), end user location (e.g. continent, country, state/providence, city, zip, and/or the like), time (e.g. end user time, advertiser time, coordinated universal time (UTC), and/or the like), end user interests (e.g. sports, politics, and/or the like), and/or the like, and/or combinations thereof. Such user publisher centric data may include or otherwise be associated with publication content (e.g. shopping, search, and/or the like), publication Uniform Resource Locator (URL), publication domain, publication site, and/or the like, and/or combinations thereof.
For a given request for advertisement, an associated current context may be modeled as a map of a given target dimension portion and given target value portion. Likewise, for a given premium rule, an associated target dimension may be modeled as a map of a given target dimension portion and given target value portion. Such a target dimension may identify a particular current context in the above taxonomy of a given request for advertisement. For example, such a target dimension may identify a time-type current context. Such a target value may be a computed value representing a quantification of the given target dimension of a given request for advertisement. For example, such a target value may be computed to represent a quantification of a time-type current context. For example, end user time could be represented as a number of minutes within a week, such as one for 0:01 AM Monday, sixty-one for 1:01 AM Monday, and/or the like. Such a map of a current context may be compared with target dimensions associated with one or more premium rules. Based at least in part on such a comparison, such premium rules may determine at least a portion of the cost of such advertising. As will be described in greater detail below, in some embodiments such premium rules may be formed as decision trees associated with a single target dimension (referred to herein as basic premium rules) or may be formed as decision trees associated with two or more target dimensions (referred to herein as composite premium rules).
Ad manager 106 may determine which ads to send to end users 110 based at least in part on information received from advertisers. Such ad units may be filtered and/or ranked by ad manager 106 based on one or more criteria. For example such ad units may be filtered and/or ranked based on criteria from advertiser device 104, publisher device 108, and/or based on end user data. Additionally, ad manager 106 may determine a cost of such advertising based at least in part on information received from advertisers, as illustrated at action 120. As will be described in greater detail below, such information may include premium rule related information associated with a given ad unit. Such premium rule related information may include one or more constraints or rules that may determine the cost of such advertising based on a determination of one or more target dimensions. Ad manager 106 may send a response to user requests for advertisements to end users 110, as illustrated at action 122. For example, such a response to user requests for advertisements may include an ad, and may also include an associated premium value that may be embedded within the response.
Referring to
Here, hierarchical node structure 200 may express and/or represent hierarchical information within one or more computing platforms by digital electronic signals, and/or the like, for example. By way of example but not limitation, information in such a hierarchical node structure 200 may be expressed as a finite, rooted, connected, acyclic graph. Such a hierarchical ad node structure 200 may include a node (e.g., a root node) that may not have any preceding parent nodes. For example, an account-type node 202 associated with a given advertising account may be utilized as such a root node. Additionally, hierarchical node structure 200 may be traversed via edges 212 to reach a given leaf node. A leaf node may refer to a node that may not have any subsequent child nodes. For example, ad-group-type nodes 206 and/or keyword-term-type nodes 208 may be associated with a given advertising account to be utilized as a leaf node to represent a possible base bid data 212 associated with a given ad unit. Thus, a path through hierarchical node structure 200 may pass from a root node to a given leaf node. Additionally, hierarchical node structure 200 also may include interior nodes located between a root node to a given leaf node that may have a preceding parent node, such as a root node or another interior node, and also may have subsequent child nodes, such as leaf nodes or other interior nodes. For example, campaign-type nodes 204 associated with a given advertising account may be utilized as such an interior node (additional ad-group-type nodes 206, keyword-term-type nodes 208, and/or creative-component-type nodes 210 associated with individual campaign-type nodes 204 may not be illustrated here).
Such hierarchical node structures 200 may be utilized to access base bid data associated with a given item of advertising. For example, such base bid data may be utilized to sorts various ad units according to a baseline price associated with a given ad unit. Ad manager 106 (
Referring to
Additionally, one or more premium rules 216 may be associated with one or more nodes 202/204/206 of hierarchical node structure 200. Such premium rules 216 may be utilized to determine one or more premium markup values associated with a given item of advertising. Ad manager 106 (
Referring to
where “target_dimension_ID” refers to a target dimension, “target_min_value” refers to a minimum target value, “target_max_value” refers to a maximum target value, and “premium_value” refers to a monetary-value-type and/or a percentage-type premium markup. In the above example, such a maximum target value may be optional. As discussed above, for a given request for advertisement, an associated current context may be modeled as a map of a given target dimension and given target value. Likewise, for a given premium rule, an associated target dimension may be modeled as a map of a given target dimension and given target value. As illustrated, such a hierarchical target node structure 300 may be described as follows:
Referring to
As illustrated, such composite premium rules represented in a hierarchical target node structure 400 may be described as follows:
where “target_dimension_ID” refers to a target dimension, “target_min_value” refers to a minimum target value, “target_max_value” refers to a maximum target value, and “premium_rule” refers to an additional embedded rule. As illustrated, such a hierarchical target node structure 400 may be described as follows:
where “interests::Sports” refers to a target dimension of an end user interest (e.g. sports) associated with negative minimum target value of zero and a positive maximum target value of one. With a negative minimum target value of zero, “time::localTime” refers to a second target dimension of an end user time where “9 am-5 pm” refers to a target value of time associated with a monetary-value-type premium markup of twenty five cents. Similarly, with a positive maximum target value of one, “time:: localTime” refers to a second target dimension of an end user time where (“11 am”, “12:59 pm”) refers to a target value range of time associated with a monetary-value-type premium markup of one dollar and where (“1 pm”, “4:59 pm”) refers to a target value range of time associated with a monetary-value-type premium markup of two dollars.
Referring back to
Referring back to
Process 500, as illustrated in
Process 500, depicted in
At block 504, advertising data may be received, where such advertising data may associate one or more premium rules with one or more nodes of such a hierarchical node structure. As discussed above, such premium rules may include a hierarchical target node structure including two or more target dimensions. For example, two or more premium rules may be associated to an ad unit at one or more of the following hierarchical nodes: an account-type node, a campaign-type node, and/or an ad-group-type node and/or the like. To avoid potential conflict among premium rules, a group of two or more premium rules 216 may be forbidden from reusing identical target dimension sets.
For a premium rule, its hierarchical target node structure may include one or more target nodes associated with a first target dimension and one or more nodes associated with a second target dimension. For example, such a first and second target dimensions may be restrained so that a comparison of a current context to such two or more target dimensions may match no more than one target node associated with a first target dimension and no more than one target node associated with a second target dimension.
At block 506, base bid data associated with a node of such a hierarchical ad node structure may be accessed. As discussed above, such a node may be associated with at least a portion of an ad unit. For example, such a node may include a keyword-term-type node associated with a keyword term portion of an ad unit. Additionally or alternatively, such a node may include an ad-group-type node associated with an ad unit. As discussed above, such target dimensions may include one or more of the following: an end user demographic, end user location, time, end user interests, publication content, publication Uniform Resource Locator (URL), publication domain, publication site, and/or the like, and/or combinations thereof.
At block 507, preliminary conditions may be set. For example, an initial total bid may be set as equal to an accessed base bid value. Additionally, a current node of the hierarchical ad node structure may be specified. For example, such a current node may be specified as a keyword-term-type node associated with a keyword term portion of an ad unit. Further, a set of tested target dimensions may be reset.
At block 508, a subset of premium rules associated with such a current node may be identified. As discussed above, potential conflicts between multiple premium rules and/or potential conflicts multi-level association of premium rules may be resolved by providing one or more conflict resolution features for premium rules. One such conflict resolution feature may include forbidding a group of two or more premium rules from reusing identical target dimension sets. Such a group of two or more premium rules may include those premium rules identified and/or evaluated climbing up a hierarchical node structure, for example. Such target dimensions from identified and/or evaluated premium rules may be remembered. Precedence may be given to premium rules in the order that such premium rules were identified and/or evaluated, such as in a bottom-up order climbing up a hierarchical node structure, for example. For example, for a premium rule that has been evaluated to be relevant to a given current context, an associated target dimension set may be remembered. A subsequently identified premium rule may be ignored.
Accordingly, a premium markup data may be determined based at least in part on such identified premium rules. For example such premium markup data may be determined based at least in part on one or more premium rules comparing a current context associated with a given end user to two or more target dimensions. For example, such premium markup data may be based at least in part on a percentage-type premium markup, such as a percentage of base bid data. Alternatively, such premium markup data may be based at least in part on monetary values independent of base bid data. As discussed above, such current contexts may include an end user demographic, end user location, time, end user interests, publication content, publication Uniform Resource Locator (URL), publication domain, publication site, and/or the like, and/or combinations thereof.
At block 510, a total bid may, for example, be determined based at least in part on combining premium markup data with base bid data. In some cases, such base bid data may be represented by an initial total bid that was set to be equal to a base bid at block 507, for example. Additionally, in situations where there is not applicable premium markup, such a total bid may be based only on base bid data. Such a total bid may be utilized to charge an advertiser for delivering a given ad to an end user.
At block 512, a set of tested target dimensions may be updated. For example, a set of tested target dimensions may be updated to included those dimensions tested at block 508.
At block 514, a determination may be made to see if process 500 has reached a root of the hierarchical ad node structure. In cases where such a root has been reached, process 500 may end. In cases where such a root has not been reached, a parent node may be set to be the current node to be analyzed and process 500 may return to block 508 for further operations, as illustrated at block 516,
In operation, process 500 may be utilized to provide a flexible and structured mechanism for advertisers (and/or other like entities) to control premium markups associated with a targeting of certain publishers, pages and/or end users. For example, the mechanism, illustrated by process 500, may allow for a flexible and extensive taxonomy for target dimensions include various combinations of the following: an end user demographic, end user location, time, end user interests, publication content, publication Uniform Resource Locator (URL), publication domain, publication site, and/or the like, and/or combinations thereof. For example, in some embodiments, premium rules may be formed as decision trees associated with a single target dimension (referred to herein as basic premium rules) and/or as decision trees associated with two or more target dimensions (referred to herein as composite premium rules). Additionally, multi-level association of premium rules 216 with hierarchical node structure 200 may be facilitated by providing a conflict resolution between premium rules 216. For example, a group of two or more premium rules 216 may be forbidden from reusing identical target dimension sets. Further, a hierarchical target node structure may include one or more target nodes associated with a first target dimension and one or more nodes associated with a second target dimension. In such a case, such a first and second target dimensions may be restrained so that a comparison of a current context to such two or more target dimensions may match no more than one target node associated with a first target dimension and no more than one target node associated with a second target dimension.
Computing environment system 600 may include, for example, a first device 602, a second device 604 and a third device 606, which may be operatively coupled together through a network 608.
First device 602, second device 604 and third device 606, as shown in
Network 608, as shown in
As illustrated by the dashed lined box partially obscured behind third device 606, there may be additional like devices operatively coupled to network 608, for example.
It is recognized that all or part of the various devices and networks shown in system 600, and the processes and methods as further described herein, may be implemented using or otherwise include hardware, firmware, software, or any combination thereof.
Thus, by way of example, but not limitation, second device 604 may include at least one processing unit 620 that is operatively coupled to a memory 622 through a bus 623.
Processing unit 620 is representative of one or more circuits configurable to perform at least a portion of a data computing procedure or process. By way of example, but not limitation, processing unit 620 may include one or more processors, controllers, microprocessors, microcontrollers, application specific integrated circuits, digital signal processors, programmable logic devices, field programmable gate arrays, and the like, or any combination thereof.
Memory 622 is representative of any data storage mechanism. Memory 622 may include, for example, a primary memory 624 and/or a secondary memory 626. Primary memory 624 may include, for example, a random access memory, read only memory, etc. While illustrated in this example as being separate from processing unit 620, it should be understood that all or part of primary memory 624 may be provided within or otherwise co-located/coupled with processing unit 620.
Secondary memory 626 may include, for example, the same or similar type of memory as primary memory and/or one or more data storage devices or systems, such as, for example, a disk drive, an optical disc drive, a tape drive, a solid state memory drive, etc. In certain implementations, secondary memory 626 may be operatively receptive of, or otherwise configurable to couple to, a computer-readable medium 628. Computer-readable medium 628 may include, for example, any medium that can carry and/or make accessible data, code and/or instructions for one or more of the devices in system 600.
Second device 604 may include, for example, a communication interface 630 that provides for or otherwise supports the operative coupling of second device 604 to at least network 608. By way of example, but not limitation, communication interface 630 may include a network interface device or card, a modem, a router, a switch, a transceiver, and the like.
Second device 604 may include, for example, an input/output 632. Input/output 632 is representative of one or more devices or features that may be configurable to accept or otherwise introduce human and/or machine inputs, and/or one or more devices or features that may be configurable to deliver or otherwise provide for human and/or machine outputs. By way of example, but not limitation, input/output device 632 may include an operatively enabled display, speaker, keyboard, mouse, trackball, touch screen, data port, etc.
Some portions of the detailed description are presented in terms of algorithms or symbolic representations of operations on data bits or binary digital signals stored within a computing system memory, such as a computer memory. These algorithmic descriptions or representations are examples of techniques used by those of ordinary skill in the data processing arts to convey the substance of their work to others skilled in the art. An algorithm is here, and generally, is considered to be a self-consistent sequence of operations or similar processing leading to a desired result. In this context, operations or processing involve physical manipulation of physical quantities. Typically, although not necessarily, such quantities may take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared or otherwise manipulated. It has proven convenient at times, principally for reasons of common usage, to refer to such signals as bits, data, values, elements, symbols, characters, terms, numbers, numerals or the like. It should be understood, however, that all of these and similar terms are to be associated with appropriate physical quantities and are merely convenient labels. Unless specifically stated otherwise, as apparent from the following discussion, it is appreciated that throughout this specification discussions utilizing terms such as “processing,” “computing,” “calculating,” “determining” or the like refer to actions or processes of a computing platform, such as a computer or a similar electronic computing device, that manipulates or transforms data represented as physical electronic or magnetic quantities within memories, registers, or other information storage devices, transmission devices, or display devices of the computing platform.
In one implementation, premium rules may associate premium markup data to base bid data for online advertising via a computing platform. Such premium ruling may be performed via a computing platform that manipulates or transforms electronic signals employed to represent physical electronic or magnetic quantities, or other physical quantities, within the computing platform's memories, registers, or other information storage, transmission, or display devices. For example, a computing platform may be enabled to receive advertising data that associates an online advertising budget among one or more ad units in a hierarchical node structure represented within one or more computing platforms by digital electronic signals. Such a computing platform may additionally be enabled to receive advertising data that associates one or more premium rules represented within such computing platforms by digital electronic signals with one or more nodes of such a hierarchical node structure. Such a computing platform may additionally be enabled to access base bid data represented within such computing platforms by digital electronic signals associated with a node of such a hierarchical node structure. Such a computing platform may additionally be enabled to determine premium markup data represented within such computing platforms by digital electronic signals based at least in part on a comparison via such premium rules of a current context associated with a given end user to such target dimensions
Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of claimed subject matter. Thus, the appearance of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
The term “and/or” as referred to herein may mean “and”, it may mean “or”, it may mean “exclusive-or”, it may mean “one”, it may mean “some, but not all”, it may mean “neither”, and/or it may mean “both”, although the scope of claimed subject matter is not limited in this respect.
While certain exemplary techniques have been described and shown herein using various methods and systems, it should be understood by those skilled in the art that various other modifications may be made, and equivalents may be substituted, without departing from claimed subject matter. Additionally, many modifications may be made to adapt a particular situation to the teachings of claimed subject matter without departing from the central concept described herein. Therefore, it is intended that claimed subject matter not be limited to the particular examples disclosed, but that such claimed subject matter also may include all implementations falling within the scope of the appended claims, and equivalents thereof.