Patent Publication Number: US-2010125597-A1

Title: System and method for determining search terms for use in sponsored searches

Description:
BACKGROUND 
     Internet advertising may implement the use of graphical ad campaigns. The graphical ad campaigns may be categorized into brand advertising campaigns and direct marketing campaigns. In brand advertising campaigns, brand advertisers may be interested in generating brand awareness. A strategy may be to present a brand through graphical ads to as many individuals as possible in hopes of increasing the brand popularity. In direct marketing campaigns, advertisers may be concerned with individuals responding directly to an Internet ad, such as by clicking on a universal resource locator (“URL”), allowing an individual to immediately purchase goods or services through selection of a graphical ad. 
     Brand advertisers may not be interested in participating in direct marketing campaigns, which may include sponsored Internet searches, allowing graphical ads to be delivered to a user based on particular search terms provided to an Internet search engine by an Internet user. The brand advertiser may believe that sponsored searches generating Internet search listings may not increase popularity associated with a particular brand. However, a brand advertiser may be interested in participating in a sponsored search if the brand advertiser believed specific search terms may be relevant to a particular brand. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram of one example of an environment in which a system for determining search terms for a sponsored search; 
         FIG. 2  is a block diagram of one embodiment of a system for determining search terms for a sponsored search; 
         FIG. 3  is a block diagram of one example of a search term recommendation module; 
         FIG. 4  is a flow chart of one embodiment of a method for recommending search terms for a sponsored search; and 
         FIG. 5  is a block diagram of one embodiment of a computer system. 
     
    
    
     DETAILED DESCRIPTION OF THE DRAWINGS 
     The present disclosure is directed to systems and methods for determining recommended search terms for a sponsored search. An online advertisement service provider (“ad provider”) may desire to determine search terms for a sponsored search based on Internet user interest in a digital Internet ad. A search term recommendation module may record search terms used by Internet users served the digital Internet ad. The search term recommendation module may determine a correlation between subject matter of the digital Internet ad and search terms used by the Internet users served the digital Internet ad. The correlation may be used to recommend search terms to an advertiser for sponsored searches concerning subject matter of the digital Internet ad. 
     The environment  100  may include a plurality of advertisers  102 , an ad campaign management system  104 , an ad provider  106 , a search engine  108 , a website provider  110 , and a plurality of Internet users  112 . Generally, an advertiser  102  bids on terms and creates one or more digital ads by interacting with the ad campaign management system  104  in communication with the ad provider  106 . The advertisers  102  may purchase digital ads based on an auction model of buying ad space or a guaranteed delivery model by which an advertiser pays a minimum cost-per-thousand impressions (i.e., CPM) to display the digital ad. Typically, the advertisers  102  may pay additional premiums for certain targeting options, such as targeting by demographics, geography, technographics or context. The digital ad may be a graphical banner ad that appears on a website viewed by Internet users  112 , a sponsored search listing that is served to an Internet user  112  in response to a search performed at a search engine, a video ad, a graphical banner ad based on a sponsored search listing, and/or any other type of online marketing media known in the art. 
     When an Internet user  112  performs a search at a search engine  108 , the search engine  108  may return a plurality of search listings to the Internet user. The ad provider  106  may additionally serve one or more digital ads to the Internet user  112  based on search terms provided by the Internet user  112 . In addition or alternatively, when an Internet user  112  views a website served by the website provider  110 , the ad provider  106  may serve one or more digital ads to the Internet user  112  based on keywords obtained from the content of the website. 
     When the search listings and digital ads are served, the ad campaign management system  104 , the ad provider  106 , and/or the search engine  108  may record and process information associated with the served search listings and digital ads for purposes such as billing, reporting, or ad campaign optimization. For example, the ad campaign management system  104 , ad provider  106 , and/or search engine  108  may record the search terms that caused the search engine  108  to serve the search listings; the search terms that caused the ad provider  106  to serve the digital ads; whether the Internet user  112  clicked on a URL associated with one of the search listings or digital ads; what additional search listings or digital ads were served with each search listing or each digital ad; a rank of a search listing when the Internet user  112  clicked on the search listing; a rank or position of a digital ad when the Internet user  112  clicked on a digital ad; and/or whether the Internet user  112  clicked on a different search listing or digital ad when a digital ad, or a search listing, was served. One example of an ad campaign management system that may perform these types of actions is disclosed in U.S. patent application Ser. No. 11/413,514, filed Apr. 28, 2006, and assigned to Yahoo! Inc., the entirety of which is hereby incorporated by reference. It will be appreciated that the systems and methods for determining search terms described below may operate in the environment of  FIG. 1 . 
     In the environment  100 , some types of advertisers, such as brand advertisers may not be interested in digital ads being delivered based on a sponsored search. Instead, the brand advertisers may be interested in purchasing digital ads based on the auction model of buying ad space or the guaranteed delivery model by which an advertiser pays a minimum cost-per-thousand impressions (i.e., CPM) to display the digital ad, as described above. However, a brand advertiser may be interested in delivering a digital ad based on a sponsored search if particular search terms were identified as having some correlation with an Internet user  112  identified as having an interest in the brand advertiser&#39;s particular brand or brands. The environment  100  may be configured to determine a correlation between a digital ad and search terms that may be more relevant for a sponsored search regarding the subject matter of the graphical ad. 
       FIG. 2  is a block diagram of one embodiment of a system  200  for recommending search term to an advertiser for use in a sponsored search. The system  200  may include a search engine  202 , a website provider  204 , an ad provider  206 , and an ad campaign management system  208 . In some implementations, the ad campaign management system  208  may be part of the search engine  202 , website provider  204 , and/or ad provider  206 . However, in other implementations, the ad campaign management system  208  is distinct from the search engine  202 , website provider  204 , and/or ad provider  206 . 
     The search engine  202 , website provider  204 , ad provider  206 , and ad campaign management system  208  may communicate with each other over one or more external or internal networks. The networks may include local area networks (LAN), wide area networks (WAN), and the Internet, and may be implemented with wireless or wired communication mediums such as wireless fidelity (WiFi), Bluetooth, landlines, satellites, and/or cellular communications. Further, the search engine  202 , website provider  204 , ad provider  206 , ad campaign management system  208  may be implemented as software code running in conjunction with a processor such as a single server, a plurality of servers, or any other type of computing device known in the art. 
     As described in more detail below, an advertiser  210  may provide a digital ad  212  that may be provided to a plurality of Internet users  214 . In  FIG. 2 , the digital ad  212  may be served to each of a plurality of Internet users  214  based on the auction model of buying ad space or the guaranteed delivery model to display the digital ad, as previously described. In one example, the digital ad  212  may be provided to the Internet users  214  through the website provider  204  and/or ad provider  206 . In the example of  FIG. 2 , the system  200  may include a number Z different Internet users  214 . Of these Z Internet users  214 , a subset  216  of N Internet users  214  may be served with the digital ad  212 . 
     A search term recommendation module  209  may identify the Internet users  214  served with the digital ad  212 . In one example, the search term recommendation module  209  may be executed by ad campaign management system  208 . In alternative examples, the search term recommendation module  209  may be executed by the ad provider  206  or other suitable system. In one example, each Internet user  214  may be identified by the search term recommendation module  209  through a respective cookie  218  allowing various Internet activities conducted by each Internet user  214  to be tracked. Such Internet activities may include performing Internet searches using various search terms  220 . The search terms  220  may be one or more string of characters used as input to an Internet search through a search engine  202 . 
     Internet activity of the subset  216  of Internet users  214  may be tracked and stored by the search term recommendation module  209  as indicated by table  222 . In alternative examples, the website provider  204 , the ad provider  206 , or the search engine  202  may each be used to track and store the number of times each Internet user  214  performs an Internet search using a particular search term  220  and relay the information to the search term recommendation module  209 . The particular search terms  220  are designated as search terms  1  through K in the table  222  for purposes of illustration. The number of times each Internet user  214  of the subset  216  selects, or clicks, on the digital ad  212  may also be stored by search term recommendation module  209  as indicated by the field “Click Count” in the table  222 . In one example, the subset  216  of Internet users  214  may be predetermined so that, once N Internet users  214  have been served the digital ad  212 , no other Internet users  214  are monitored even if served with the digital ad  212 . In another example, the subset  216  may represent N Internet users  214  to have clicked on the digital ad  212 . In another example, once the subset  216  of Internet users are selected, the Internet activity of each Internet user  214  in the subset  216  may be monitored and the search terms and click counts may be obtained over a predetermined amount of time. 
     The Internet activity associated with the subset  216  of the Internet users  214  may be processed to determine search terms that may be recommended to an advertiser associated with the digital ad  212  and/or used in a sponsored search. In one example, the search term recommendation module  209  may determine a correlation level between each search term  1  through K and the digital ad  212 . This correlation level may vary search term by search term, which may indicate that particular ones of search terms  1  through K are more relevant to subject matter advertised through a digital ad  212 . The search terms  1  through K having relatively higher correlation levels may be more desirable for an advertiser to bid upon for purposes of a sponsored search. 
     In one example, the search term recommendation module  209  may use the information in the table  222  to determine the correspondence level between each search term  220  and the digital ad  212 .  FIG. 3  depicts an example of the search term recommendation module  209  configured to determine a correlation level between each search term  1  through K and the digital ad  212  in the form of a corresponding weighting factor. The search term recommendation module  209  may utilize the data obtained based on the Internet user activity as summarized in table  222 , which includes the click count for each Internet user  214  of the subset  216  and a number of times each search term  1  through K is used for an Internet search by each of the Internet users  214  of the subset  216 . 
     The search term recommendation module  209  may implement a classification tool  224 , which may determine the weighting factor for each search term  1  through K. In one example, the classification tool may utilize a classification technique, such as a linear regression for example, in determining a weighting factor. In alternative examples, other classification techniques may be applied such as rule based, regression trees, neural networks, Bayesian networks, or other suitable technique, for example. The linear regression technique may be used to establish a relationship between the click counts and number of searches performed with each search term  1  through K. In one example, the relationship may be established through the following equation: 
         Y=XB+ε   EQN. (1) 
     where Y is the click count for one of the Internet users  214  of the subset  216 , X is an array of the numbers of Internet searches performed by an Internet user  214  of the subset  216  for each search term  1  through K; B is an array of weighting factors that represent the level of correspondence between each search term  1  through K and the click count; and ε represents an error factor. 
     The linear regression technique may be used for each Internet user  1  through N allowing the weighting factor B for each search term  1  through K to be determined. The weighting factor B may be a number between 0 and 1, with all of the weighting factors associated with each Internet user  214  summing to approximately 1. Upon determining the weighting factors for each search term  1  through K, the search terms  1  through K may be ranked according to weighting factor. The search term or terms having the highest weighting factor may have the highest rank. The search term or terms  1  through K having the rank, and thus, the relatively highest weighting factor(s), may be the search terms recommended to the advertiser  202  for use in a sponsored search. Table  226  illustrates the weighting factors, designated individually as WF ST1  through WF STK  in the table  226 , corresponding to each search term  1  through K, designated as ST 1  through STK in the table  226 . 
       FIG. 4  depicts a method  400  of determining search terms to recommend to an advertiser for use in a sponsored search. The method  400  may include a step  402  of serving a digital ad. In one example, step  402  may include serving a digital ad to a number of Internet users. The digital ad may be served to an Internet user based on the auction model of buying ad space or a guaranteed delivery model to display the digital ad, for example. The method  400  may also include a step  404  of determining the number of Internet users served the digital ad. In one example, the step  404  may be performed through a system such as the system  200  shown in  FIG. 2 . The search term recommendation module  209  of the system  200  may track and store the number of Internet users  214  being served the ad based on a cookie  218  of each Internet user  214 . 
     The method  400  may include a step  406  of determining if the desired number of Internet users to receive the digital ad has been reached. In one example, a predetermined number may be selected as a limit on the number of Internet users served the digital ad that are to be tracked. If the desired number has not been reached in step  406  then loop  407  may return the method  400  to step  404  to continue determining the number of Internet users to receive the digital ad. In one example, step  406  may continue to be performed while other steps of the method  400  are performed. 
     The method  400  may include a step  408  of determining each search term used by each of the Internet users served the digital ad. In one example, step  408  may be performed by tracking and storing search terms used by each Internet user that has been served with the digital ad. The method  400  may include a step  410  of determining a number of times each Internet user served with the digital ad clicks on the digital ad. Steps  408  and  410  may be performed with a system, such as the system  200  of  FIG. 2 . In one example, the steps  408  and  410  may be performed by the ad campaign management system  208 . 
     The method  400  may include a step  412  of determining a correlation level between each search term and the digital ad. In one example, step  412  may include determining a correlation level between search terms and the digital ad by performing a classification technique on information regarding the number of times each Internet user has clicked on the digital ad and the search terms used by the Internet user, such as that described in regard to  FIGS. 2 and 3 , for example. The classification technique may provide weighting factors associated with each search term representing the correlation levels. A weighting factor associated with a particular search word may indicate the level of correlation between that particular search word and the digital ad. 
     The method  400  may include a step  414  of determining if a predetermined time has elapsed. In one example, the correspondence levels may continuously be updated until a predetermined time has elapsed, which then allows final correspondence values to be determined at step  414 . If the predetermined time has not elapsed, loop  415  may return to step  408 . Once the predetermined amount of time has elapsed, step  416  of the method  400  may be performed, which includes recommending search terms for sponsored searches based on the correlation levels. In one example, a search term having the highest correlation level may the most highly recommended term. As described in  FIGS. 2 and 3 , a search term  220  having the highest weighting factor as compared to the weighting factors of the other search terms  220  may have the highest rank among recommended search terms. Thus, the search term(s) with the highest rank (e.g., highest weighting factor) may be the first search term(s) recommended. The search term(s) with the next highest rank may be the next recommended search term, and so forth. This configuration allows search terms for to be recommended to an advertiser of the digital ad for purposes of becoming involved with a sponsored search based on subject matter in a digital ad. 
     Any of the modules, servers, or engines described may be implemented in one or more general computer systems. One exemplary system is provided in  FIG. 5 . The computer system  500  includes a processor  510  for executing instructions such as those described in the methods discussed above. The instructions may be stored in a computer readable medium such as memory  512  or a storage device  514 , for example a disk drive, CD, or DVD. The computer may include a display controller  516  responsive to instructions to generate a textual or graphical display on a display device  518 , for example a computer monitor. In addition, the processor  510  may communicate with a network controller  520  to communicate data or instructions to other systems, for example other general computer systems. The network controller  520  may communicate over Ethernet or other known protocols to distribute processing or provide remote access to information over a variety of network topologies, including local area networks, wide area networks, the internet, or other commonly used network topologies. 
     In an alternative embodiment, dedicated hardware implementations, such as application specific integrated circuits, programmable logic arrays and other hardware devices, can be constructed to implement one or more of the methods described herein. Applications that may include the apparatus and systems of various embodiments can broadly include a variety of electronic and computer systems. One or more embodiments described herein may implement functions using two or more specific interconnected hardware modules or devices with related control and data signals that can be communicated between and through the modules, or as portions of an application-specific integrated circuit. Accordingly, the present system encompasses software, firmware, and hardware implementations. 
     In accordance with various embodiments of the present disclosure, the methods described herein may be implemented by software programs executable by a computer system. Further, in an exemplary, non-limited embodiment, implementations can include distributed processing, component/object distributed processing, and parallel processing. Alternatively, virtual computer system processing can be constructed to implement one or more of the methods or functionality as described herein. 
     Further the methods described herein may be embodied in a computer-readable medium. The term “computer-readable medium” includes a single medium or multiple media, such as a centralized or distributed database, and/or associated caches and servers that store one or more sets of instructions. The term “computer-readable medium” shall also include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor or that cause a computer system to perform any one or more of the methods or operations disclosed herein. 
     As a person skilled in the art will readily appreciate, the above description is meant as an illustration of the principles of this invention. This description is not intended to limit the scope or application of this invention in that the invention is susceptible to modification, variation and change, without departing from spirit of this invention, as defined in the following claims.