Identification and Management of Parasitic Ads for Improving the Effectiveness of Internet Ads

Abstract

generating a cannibalization score for paid advertisements in a SERP by the steps of: collecting keywords related to an advertiser; defining rules for calculating a cannibalization score for advertisements associated with a corresponding unpaid listing, wherein the cannibalization score estimates a reduction in revenue to the advertiser due to the advertisement appearing in the same search engine results page (SERP) as the corresponding listing; providing the keywords to a search engine; receiving a SERP from the search engine; identifying the location of a first advertisement placed by the advertiser among one or more advertisements in the SERP; identifying the location of the corresponding unpaid listing among multiple unpaid listings in the SERP; and applying the rules to the advertisements and the corresponding unpaid listings to obtain a cannibalization score for the advertisements.

Description

Technical Field

[0001] The present invention relates to online advertising technology, and more particularly, to the ability to identify and manage the purchase of cannibalistic ads within a web page.

Background Art

[0002] An Internet search engine responds to a keyword search performed by a user by returning one or more web pages to the user's browser. The returned web pages are known as "search engine results pages" or SERPs (search engine results pages), and generally include free search listings, also called "organic" search results, and paid advertisements, also called ads. Each listing includes a URL related to the search terms entered by the user, or a link to a World Wide Web page. The web page corresponding to the URL returned in a paid advertisement or free listing within a SERP is often referred to as a landing page.

[0003] The purpose of online advertising is to induce a user to click on a paid advertisement and visit the advertiser's website. The effectiveness of an online advertising campaign is usually measured as a function of the number of clicks on paid listings corresponding to the number of visitors to the website resulting from the advertising campaign, and the amount of revenue generated by those visitors. The effectiveness of an advertising campaign can be measured by the ratio of the revenue generated to the advertising cost, or by the ratio of the visitors to the advertising cost.

[0004] However, the effectiveness of an advertising campaign can be significantly limited by cannibalistic ads, which are ads that lead to additional costs by diverting visitors who would otherwise visit a free listing as a result of clicking on a free listing to a paid advertisement. In other words, cannibalistic ads increase the advertiser's cost by diverting visitors from a free listing to the cannibalistic ad.

[0005] In its most basic form, a cannibalistic ad is an ad purchased by an advertiser that appears on a web page next to a free listing that promotes the same service or product as the paid ad. Sometimes, users click on the paid ad instead of the free listing. As a result, assuming what percentage of cases the user would have clicked on the free listing, unnecessary advertising costs would be incurred by the advertiser. In other cases, there may be one or more ads between the advertiser's ad and the corresponding free listing. Even in such cases, the paid ad can still be considered cannibalistic. Therefore, it is advantageous to identify cannibalistic ads so that the advertiser can determine whether to purchase such cannibalistic ads.

[0006] Since the cannibalistic ad spend is a new metric for judging the effectiveness of an advertising campaign, in addition to detecting cannibalistic ads, it is desirable to determine the amount of money the advertiser spent on purchasing cannibalistic ads. Such a value enables the advertiser to judge the magnitude of the problem and reduce the advertiser's expenditure on cannibalistic ads without compromising the effectiveness of the advertiser's advertising campaign. SUMMARY OF THE INVENTION MEANS FOR SOLVING THE PROBLEM

[0007] A method, system, and device for measuring the amount of money an advertiser spent on purchasing a cannibalistic ad (ad), and the amount of money, called reclaimed ad spend, that can be recovered by not purchasing the cannibalistic ad.

[0008] In some embodiments, the method calculates a cannibalization score for ads within a search engine results page (SERP), where the cannibalization score estimates the likelihood that a paid ad is a cannibal, i.e., the likelihood that the paid ad appears near the corresponding unpaid listing. In other embodiments, the cannibalization score estimates a reduction in revenue to the advertiser due to the appearance of a paid cannibal ad within the same SERP as the corresponding unpaid listing.

[0009] Some embodiments are directed to generating a cannibalization score for a paid ad within a SERP by collecting keywords relevant to an advertiser, defining rules for calculating a cannibalization score for ads related to the corresponding unpaid listing, where the cannibalization score estimates a reduction in revenue to the advertiser due to an ad appearing within the same search engine results page (SERP) as the corresponding listing, providing the keywords to a search engine, receiving a SERP from the search engine, identifying the position of a first ad posted by the advertiser from among one or more ads within the SERP, identifying the position of the corresponding unpaid listing from among a plurality of unpaid listings within the SERP, and applying the rules to the ad and the corresponding unpaid listing to obtain a cannibalization score for the ad.

[0010] Some embodiments are directed to generating an estimated cost recovery value for an Internet advertising campaign by: receiving a set of keywords, each keyword corresponding to a paid advertisement supplied to a search engine; collecting a cannibalization score for each paid advertisement, the cannibalization score indicating that the presence of the paid advertisement designated within a SERP decreases the probability that a user clicks on the corresponding free listing; estimating the recovered advertising cost as the difference between the actual revenue reported over a period of time and the estimated value of the advertising cost for a comparable period in which non-cannibalization actions were taken; and reporting the estimated value of the recovered advertising cost.

[0011] An embodiment is a computer-implemented method for estimating the effectiveness of an Internet advertising campaign, the method comprising the steps of receiving a plurality of keywords, each keyword corresponding to a paid advertisement supplied to a search engine, the paid advertisement including a link to a web page, in response to receiving a keyword from a web browser, the search engine returning a search engine results page (SERP) including (1) the corresponding paid advertisement and (2) at least one free listing, the free listing including a link to a web page, the web page being within a domain; (1) a cannibalization score for a specified paid advertisement, the cannibalization score indicating that the presence of the specified paid advertisement in the SERP decreases the probability that a user will click on the corresponding free listing, the corresponding free listing having a linked web page within the same domain as the linked web page of the specified paid advertisement; (2) actual revenue resulting from the number of clicks on the specified paid advertisement and any corresponding free listings in the SERP during a period in which no non-cannibalization action occurred, the non-cannibalization action occurring if the paid advertisement is not supplied to the search engine due to the cannibalization score; collecting (2) the actual revenue; estimating the recovered advertising cost for the specified paid advertisement as the difference between an estimated value of the expected cost for purchasing the specified advertisement for a certain period and the actual cost reported for a comparable period in which a non-cannibalization action was taken; and reporting an estimated value of the recovered advertising cost.

[0012] The present invention will be more fully understood and recognized by reading the following detailed description in conjunction with the drawings.

Brief Description of the Drawings

[0013]

Figure 1

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[0014] The drawings illustrate embodiments of the invention for illustrative purposes only. Those skilled in the art will readily recognize from the following explanations that alternative embodiments and combinations of embodiments of the structures and methods shown herein may be employed without departing from the principles of the invention described herein.

[0015] Next, the present invention will be described more fully hereinafter with reference to the accompanying drawings, which form a part hereof and show by way of illustration specific exemplary embodiments in which the invention may be practiced. However, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. In particular, the invention may be embodied as a method, process, system, business method, or device. Accordingly, the invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software aspects and hardware aspects. Therefore, the following detailed description should not be construed in a limiting sense.

[0016] The following terms used in this specification have the meanings given below.

[0017] It means an individual who uses a user - mobile device, PC, or other electronic device to access the services provided by the present invention via a network.

[0018] Advertiser - It refers to an individual, company, or other organization that posts or causes to be posted an online advertisement via a search engine for a product or service that they themselves are advertising, selling, or promoting.

[0019] Keyword or search term - It refers to a word, multiple words, phrase, or sentence entered by a user into a search field within a web page, also called a keyword query, and is sent to a search engine that executes the requested search and returns results. An advertiser can purchase or bid on an advertisement corresponding to the keyword, and in that case, the search engine results page (SERP) returned in response to the user entering the keyword includes the paid advertisement corresponding to the keyword posted by the advertiser.

[0020] Search engine or web search engine - It means a computer server or Internet service that typically receives a keyword as a result of a keyword query, uses the keyword to search for web pages corresponding to the keyword, and returns one or more search engine results pages (SERPs) including paid advertisements and free or organic listings.

[0021] Listing - Results from a keyword search that appear within the SERP. Each listing includes a link to the corresponding web page. Listings can be paid advertisements generated by the search engine, i.e., paid listings, or free or organic listings. Listings within the SERP are ranked, and each listing has a numerical position starting from the top position, or the 1st position, or the highest position. Unless otherwise specified, the listing position within the SERP refers to the numerical position from the top of the listings in the free search results. Thus, the 1st position is the highest position, the 2nd position is the next highest position, and so on. Paid listings have a paid listing position, and free listings have a free listing position.

[0022] Search Engine Results Page (SERP) - Refers to a list of web pages returned by a search engine in response to a keyword query. Each element in the list, i.e., each listing, typically includes a title, a URL or link to the web page, and a brief description indicating where the content on the page matches the keyword. The SERP can refer to a single web page containing a series of paid and free listings, or to the set of all links returned for a search query, which may span multiple web pages.

[0023] Landing Page - Refers to the web page whose URL corresponds to a listing within the SERP. When a user clicks on a listing within the SERP, the web browser requests and displays the corresponding landing page.

[0024] Co - eating advertisement - A paid advertisement provided within a web page by a search engine in response to a search by a user, which diverts clicks from nearby free listings. Generally, when a co - eating advertisement appears adjacent to or in proximity to a corresponding free listing, the value of the co - eating advertisement is lower compared to when the co - eating advertisement appears in the SERP and there is no corresponding free listing. In this context, value is typically measured in terms of the number of visitors, revenue from sales of the advertised product, or similar metrics. Further, the corresponding free listing is a free listing that references the same product or service advertised by the paid advertisement. As will be explained below, the links in the paid advertisement and the free listing may reference the same landing page or different landing pages.

[0025] Generalized operation The operation of some aspects of the present invention will be described below with respect to FIGS. 1 - 4.

[0026] FIG. 1 is a simplified block diagram of a co - eating advertisement system (CAS) 100 that automatically identifies co - eating advertisements and calculates potential improvements achieved by not purchasing such advertisements.

[0027] User 110 visits a website that enables the user to perform keyword searches using a web browser, herein referred to as browser 118, such as GOOGLE CHROME or Mozilla Firefox or other client applications. Browser 118 sends the keyword to search engine 120, which executes the requested search and returns a (SERP), which is then displayed by browser 118. The SERP typically includes one or more paid listings or advertisements and one or more free listings. Each advertisement or free listing corresponds to a web page, also called a landing page, that was determined by search engine 120 to match the keyword. In the case of a paid advertisement, the advertiser "buys" the keyword and provides the corresponding advertisement to advertisement server 130, which communicates with search engine 120. Thus, when user 110 enters a keyword in the search box, the search engine includes the corresponding paid advertisement in the SERP and returns it to browser 118.

[0028] The landing page belongs to a domain or website 145 hosted by a web server, simply referred to as web server 140, or a web service. Web server 140 can host multiple domains. The web page can be static, i.e., exist as a computer file in HTML format or another format, or can be generated dynamically. Further, web server 140 can provide an e-commerce transaction that enables user 110 to purchase an item or execute a transaction that generates revenue from website 145.

[0029] Advertisement server 130 provides paid advertisements to search engine 120 to include in the SERPs. The cannibalization advertisement (CA) analyzer 135 analyzes the SERPs to identify cannibalization advertisements. Generally, CA analyzer 135 generates a list of keywords for which a cannibalization advertisement could be published if purchased. The operation of CA analyzer 135 will be described in more detail below with reference to FIGS. 2-4.

[0030] It should be understood that the CA analyzer 135 can operate in a server or computer system different from the advertising server 130. Further, the advertising server 130 can be implemented as two or more physical server computers or by a cloud service such as AMAZON AWS. Further, the CA analyzer 135 can be implemented as two or more physical server computers or by a cloud service such as AMAZON AWS.

[0031] The network 150 enables various computers, servers, and services identified in the CAS 100 to exchange data. The network 150 typically refers to the public Internet, but may also refer to a private network or any combination of a private network and a public network.

[0032] FIG. 2 is an example of a search engine results page (SERP) 200 that includes cannibalistic ads. In response to the user 110 entering the search term 215 "surebuy grocery" into the browser 118, the search engine 120 returns the SERP 200. The SERP 200 includes a paid listing 210 and a free listing 220 that is an ad for a grocery store or grocery store chain named "Surebuy Grocery".

[0033] The listing 210 is the first and only paid ad included in the SERP 200. The listing 220 is a free ad 220. The free ad 220 is in the position of the first free listing within the SERP 200.

[0034] Since Ad 210 is directly above Free Listing 220, it is a cannibalistic ad. If Ad 210 did not appear above Free Listing 220, a higher percentage of users would have clicked on Free Listing 220. Therefore, even if users would have clicked on Free Listing 220 if Ad 210 did not exist within SERP 200, the advertiser paid for Ad 210. Thus, by placing Ad 210 in the position directly above Free Listing 220, the cost of the ad increased accordingly.

[0035] Example of a cannibalistic ad The case of Figure 2 where a free listing for the same product or service appears directly below a paid ad and the paid ad is in the first position is regarded as the main case of a cannibalistic ad. In this case, there is only one paid ad, i.e., the cannibalistic ad. However, there are other cases where an advertiser may consider an ad to be cannibalistic.

[0036] When determining whether a paid ad is cannibalistic, several factors can be considered. These factors include: (1) position, (2) distance, (3) appearance rate or frequency, (4) whether the landing pages are the same or different, (5) whether the ad is "friendly" or "competitive" (or neither), and (6) the increment or net revenue generated from the ad placed by the advertiser compared to the revenue generated by the organic search results. First, factors 1 - 5 will be explained, and a rule - based approach for evaluating whether an ad is cannibalistic based on these factors will be presented.

[0037] "Position" refers to the position in the search results of a paid advertisement or the corresponding free listing. As described above, the main case is when the paid advertisement and the free listing are each in the first position, that is, when the paid advertisement is in the first position among the paid advertisements and the free listing is in the first position among the free listings. However, in some cases, a paid advertisement in the second or third position and a free listing in the first position may be regarded as cannibalization.

[0038] "Distance" refers to the number of paid and free listings between a paid advertisement and a free listing. The distance can be determined as follows from the position of the paid advertisement, the total number of paid advertisements, and the position of the free listing. Distance = (#PA - Position PA) + Position UL Equation 1 Here, #PA is the number of paid advertisements, Position PA is the position of the paid advertisement being analyzed among all the paid advertisements, and Position UL is the position of the corresponding free listing among the free listings. In this example, it is understood that the paid advertisements appear sequentially above the free listings. However, similar distance metrics can also be formulated when the paid advertisements appear in a horizontal position or another geometric position on the web page.

[0039] "Appearance rate" or "appearance frequency" refers to the fact that the positions of the advertisements and free listings can change for each search. Therefore, in some embodiments, the search terms can be "sampled" over a certain period of time or number of iterations to determine the average position of the paid advertisements or free listings in the SERP provided in response to receiving a particular keyword. For example, the search can be repeated once per minute or once per hour for one day or one week to obtain the positions of the paid advertisements or free listings in the received SERP. Alternatively, the search can be repeated 100 times per day. Of course, other sampling methods can also be used.

[0040] In some cases, the landing page of a co-branded advertisement is different from the landing page of its corresponding free listing. In some cases, such advertisements are considered co-branded. In other cases, the advertiser may be testing the landing page or may simply prefer to show its own advertisement to users rather than the free listing generated by the search engine.

[0041] "Friendly" and "Competitive" Advertisements Advertisements can be categorized as "friendly" or "competitive" advertisements based on a particular advertisement posted by the advertiser. The category assigned to an advertisement can then be used as part of the determination as to whether the advertiser's advertisement is co-branded.

[0042] Example 1: In a first example, if a first company is a business partner of a second company, the first company may treat advertisements by the second company as "friendly" and agree not to advertise in competition with advertisements posted by the second company. Thus, in this example, the fact that a friendly advertisement is in any position among the paid advertisements means that the advertiser's own advertisement is co-branded. Some other examples are shown below.

[0043] Example 2: Automobile dealer B sells automobiles manufactured by automobile manufacturer A. Manufacturer A may consider advertisements by dealer B for manufacturer A's products to be friendly and may decide not to advertise when an advertisement by dealer B appears.

[0044] Example 3: Alternatively, manufacturer A may consider advertisements posted by dealer B for its own products (i.e., products of manufacturer A) to be competitive and may want to advertise directly against these advertisements, i.e., when the advertisements posted by dealer B are statistically likely to appear in the SERP.

[0045] Example 4: In the absence of competing advertisements, the advertiser considers the advertisement to be cannibalized regardless of the position of the corresponding free listing.

[0046] More generally, the advertiser can consider an advertisement posted by a particular company or organization to be friendly or competitive and enforce advertising rules based on such a determination.

[0047] Furthermore, the advertiser can easily identify the domain of the landing page for an advertisement in the SERP by scraping and then analyzing the SERPs. Thus, a friendly advertisement can be considered an advertisement having a landing page within a friendly domain, and a competing advertisement can be regarded as an advertisement having a landing page within a competing domain. Thus, in some embodiments, friendly and competing advertisements can be determined based on a list of friendly domains and a list of competing domains. In other embodiments, company names and organization names, or even product names, can be used to determine whether an advertisement is friendly or competing.

[0048] Thus, from the perspective of the advertiser, each advertisement in the SERP can be categorized as 1) its own advertisement, 2) a friendly advertisement, 3) a competing advertisement, and 4) other, i.e., an advertisement from a company, organization, or domain that is neither the advertiser's own advertisement nor a friendly advertisement nor a competing advertisement.

[0049] In some embodiments, the CA analyzer 135 analyzes only the first SERP returned by a search for a search term. Usually, there are the maximum number of paid advertisements in the SERP. For example, the GOOGLE search engine returns up to 4 advertisements in the SERP. Thus, the advertisement most frequently returned for each advertisement position can be identified. In the following description, it is assumed that the CA analyzer 135 identifies the advertisement most frequently returned for each SERP position and also identifies the category of the advertisement.

[0050] In other embodiments, each advertisement can be categorized or classified in a more general way, i.e., any number of categories other than friendly and competitive can be used.

[0051] Rules for Identifying Cannibalistic Ads Paid ads can be evaluated using rules that evaluate a cannibalization score or metric. The rules can be formulated based on the aforementioned factors, i.e., (1) the category assigned to the paid ad within the SERP, (2) the number of paid ads within the SERP, (3) the average distance from the advertiser's ad to its corresponding organic listing, and (4) the average position of the corresponding organic listing.

[0052] Table 1 shows an example of a methodology for formulating rules that can be used to evaluate whether an ad is cannibalistic using the aforementioned factors of ad position, ad category, distance, and the position of the corresponding organic listing.

[0053] In Table 1, each row represents one rule and the columns are as follows. A. is the rule number, B. is the category of the ad that appears in the first position of the first SERP, C. is the category of the ad that appears in the second position of the first SERP, D. is the average position of the organic listing corresponding to the ad posted by the advertiser, E. is the average distance between the advertiser's ad and its corresponding organic listing, F. indicates whether the advertiser's ad is considered cannibalistic (yes) or not considered cannibalistic (no) if the rule is satisfied, and column G. shows a brief description of the rule. Further, in this example, the categories that can be assigned to an ad are A - advertiser, F - friendly, C - competitive, and O - other.

[0054] In the example of Table 1, columns D and E are shown as having integer values, but in some embodiments, it should be understood that they can be real numbers or decimals based on sampled values obtained for the average position of the corresponding free listing and the average distance from the advertiser's advertisement to the corresponding free listing. Further, columns B, C, and F can alternatively have percentage, decimal, or fractional values. For example, in column B, the category value for the listing in the first position can be A(.75), F(.1), C(.1), and O(.05), indicating the ratio or percentage when the advertisement in the first position is in category A, F, C, or O.

[0055] In some embodiments, a friendly advertisement is considered to be an advertisement that has a landing page within a domain considered to be friendly, but in other embodiments, it should be further understood that specific rules can exist for a particular domain. For example, Rule 5 is evaluated based on whether an advertisement having a link to a specified domain (Dom A) appears in the first paid advertisement position or the second paid advertisement position, and whether the corresponding free advertisement is at a distance of less than 3 from the advertiser's advertisement.

[0056] Finally, when two or more rules apply to an advertisement, the cannibalization score represents the sum, average value, or weighted average value of the results of all the rules applied to the advertisement. For example, if one rule evaluates to 75% and another rule evaluates to 25%, in the simplest case, the average value of 50% is the cannibalization score of the advertisement.

[0057] Rules Based on Incremental Ad Values There can be a difference between the revenue generated from an advertisement for an advertiser and the revenue generated from the corresponding free listing. This difference can occur when the advertisement and the free listing each link to different landing pages, because if the landing pages are different, the level of effectiveness can also be different. Therefore, if the advertisement functions on average worse than the corresponding free listing, the number of advertisement clicks will on average reduce revenue by cannibalizing the number of clicks on the free listing. It is possible to determine the average value or revenue attributable to the number of advertisement clicks and the average value or revenue attributable to the number of clicks on the corresponding free listing using data sources provided by search engines such as GOOGLE ANALYTICS, GOOGLE ADWORDS, and GOOGLE SEARCH CONSOLE, which are described in more detail in Table 2 below. The average value of a click refers to the revenue expected per click or per visit by visitors to the linked landing page, i.e., the average revenue.

[0058] One rule that can be defined by an advertiser is based on the incremental or comparative value between the number of clicks on an advertisement and the number of clicks on a free listing, as defined in Equation 2 below. [(Value of advertisement click - Value of free click)] / Cost of advertisement click Equation 2 Here, if the incremental value defined by Equation 2 is greater than 1, after considering the cost of purchasing the advertisement, there is a net positive revenue from purchasing the advertisement. Therefore, a simple rule based on Equation 2 is that if the incremental value is less than 1, the advertisement is a cannibal. However, other rules can also be considered, and the rule based on the incremental value (Equation 2) can be combined with rules such as those illustrated in Table 1. Additionally, without departing from the scope of the present invention, other equations for defining the incremental value can be defined.

[0059] It will be appreciated that each block of the flowchart shown in FIG. 3 and combinations of blocks in the flowchart can be implemented by computer program instructions. These program instructions can be provided to a processor to create a machine such that the instructions executed on the processor create means for performing the actions specified in one or more blocks of the flowchart. The computer program instructions can be executed by a processor to cause the processor to execute a series of operational steps for performing the actions specified in one or more blocks of the flowchart, thereby creating a computer-implemented process or method. The computer program instructions can also cause at least some of the operational steps shown in the blocks of the flowchart to be executed in parallel. Further, some of the steps can be executed across two or more processors as may occur in a multiprocessor computer system. Still further, one or more blocks or combinations of blocks in the flowchart can be executed concurrently with other blocks or combinations of blocks, or in a different order than illustrated, without departing from the scope or spirit of the present invention.

[0060] Accordingly, the blocks of the flowchart support combinations of means for performing the specified actions, combinations of steps for performing the specified actions, and program instruction means for performing the specified actions. It will also be understood that each block of the flowchart and combinations of blocks in the flowchart can be implemented by a dedicated hardware-based system for performing the specified action or step, or by combinations of dedicated hardware and computer instructions.

[0061] FIG. 3 provides an overall method 300 for identifying co-eating advertisements and generating a co-eating score for the advertisements. The purpose of method 300 is to evaluate search engine advertisements purchased by advertisers to identify which ones are co-eating.

[0062] In step 305, the CA analyzer 135 collects a set of search terms to evaluate. These can be ads that are currently being purchased or prospective ads by the advertiser. Generally, each ad corresponds to a search term or keyword. This step can be performed in various ways. For example, when evaluating a search engine marketing (SEM) program of a specific advertiser, e.g., Surebuy (see FIG. 2), the advertiser can usually provide a list of search terms to purchase and the corresponding paid ads that appear in the resulting SERPs.

[0063] Alternatively, the search engine can also provide a set of keywords. For example, GOOGLE SEARCH CONSOLE provided by GOOGLE, INC. can provide a listing of search terms and the average search position of the ads posted in relation to each search term. Thus, for example, if one is only interested in cases where paid ads appear in the 1st and 2nd positions and the free listings are in the 1st or 2nd position, only search terms with an average position less than 2 can be evaluated.

[0064] Additional data can be obtained from the search engine. For example, GOOGLE ADWORDS provided by GOOGLE, INC. provides information including ad position, ad cost, click through rate, ad impression share, and similar metrics.

[0065] In step 310, rules for evaluating and scoring ads are generated. These rules can be similar to the rules given in Table 1 or Equation 2.

[0066] In step 315, for one of the collected search terms, a keyword search is performed on the search engine.

[0067] In step 320, a SERP is received from a search engine. It should be noted that although method 300 is applied to a single search engine, it can be executed for additional search engines of interest. Thus, method 300 is equally applicable to all search engines.

[0068] In step 325, the listings within the received SERP (paid and free) are analyzed to identify the listing positions of the paid advertisements by the advertisers and, if there are corresponding free listings, the listing positions of those corresponding free listings. In some embodiments, the search is performed iteratively, i.e., sampling is performed to obtain the average listing position. In this case, at this step, the average listing positions of the paid advertisements and the corresponding free listings are updated.

[0069] In step 330, if sampling of the average listing position is being performed, it can be determined whether further sampling is required. If required, the process returns to step 315; if not, the process proceeds to step 335.

[0070] In step 335, the rule formulated in step 310 is applied, and as a result, a cannibalization score for the paid advertisement is obtained. The cannibalization score can have various meanings. For example, in some embodiments, the cannibalization score estimates the percentage or amount of sales or revenue lost because the paid advertisement is in proximity to the corresponding listing within the SERP.

[0071] In other embodiments, the cannibalization score represents the probability that the advertisement is actually cannibalizing and reducing the revenue generated by the free listing. In such embodiments, a cannibalization score of 75 indicates that the probability that the advertisement is cannibalizing is 75%.

[0072] In other embodiments, the score can be a Boolean value (true, false) that simply indicates that the advertisement is considered to be cannibalizing.

[0073] In step 340, if not all keywords have been processed, the process returns to step 315. If all keywords have been processed, the process continues in step 345.

[0074] In step 345, a report is generated that includes a cannibalization score for each combination of keyword and paid advertisement. Such a report may include all of the keywords collected, or only those keywords determined to be cannibalizing. For example, only combinations of keywords and paid advertisements having a score higher than a given threshold may be included in the report. In some cases, the method ends at this step and the report is provided to a service company designated by an advertiser, such as the advertiser or an online advertising company.

[0075] In other embodiments, in step 350, the advertiser or the advertiser's web service company may modify the advertisement purchase of the search engine advertisement based on the report generated in step 345.

[0076] Measure of effect: Recovered advertising cost The concept of improving the effectiveness of an advertising campaign by automatically analyzing cannibalizing advertisements and whether a paid advertisement may be cannibalizing is novel. By using this measure, the cost of an advertising campaign can be significantly reduced and the effectiveness improved. Therefore, it is important that the cost reduction and effectiveness improvement due to not purchasing cannibalizing advertisements can be measured. Providing such a measure of effect to advertisers and verifying the effectiveness of adopting an automated method for identifying cannibalizing advertisements and taking appropriate actions, called non-cannibalizing actions, can be done.

[0077] Figure 4 provides an overall method 400 for determining a measure of the effectiveness of an advertising campaign based on an estimate of potential savings by not purchasing some or all of the cannibalized ads identified by method 300. Method 400 calculates a metric herein referred to as "reclaimed ad spend" that estimates the savings by not purchasing one or more paid ads determined to be cannibalized. Method 400 uses the cannibalization score determined by method 300 to determine whether to purchase an individual ad or refrain from purchasing an individual ad.

[0078] In some embodiments, method 400 calculates the reclaimed ad spend (RAS) for a set of keywords for one day (or another suitable period), and the reclaimed ad spend for one day of search terms can be defined as in Equation 3 below. RAS = Expected ad spend - Optimized ad spend Equation 3

[0079] In step 430, the expected ad spend (EAS) for one day can be calculated as follows. EAS = Average cost per click (CPC) for one day * Average click-through rate (CTR) for one day * Number of search term impressions for one day (i.e., the number of times the user searched for that keyword) Equation 4

[0080] Although a one-day period is used in some embodiments, it is understood that other periods may be used in other embodiments of the present invention.

[0081] Optimized ad spend (OAS) is the actual measured ad spend or cost and is typically reported by the search engine during the period when non-cannibalistic actions are being taken, i.e., when the cannibalization method 300 is operating. The determination of whether to purchase keywords to run paid ads is based at least in part on the cannibalization score for the keyword. The operation of method 300, including the determination not to purchase cannibalistic ads, is also referred to as taking non-cannibalistic actions. An example of a non-cannibalistic action is not purchasing a paid ad where the cannibalization score exceeds a threshold.

[0082] As an example, when method 400 is executed against an ad purchased from the GOOGLE search engine, the measure of ad cost is obtained from a service named GOOGLE ADS provided by GOOGLE.

[0083] As an example of the expected ad spend (Equation 4) for one search term per day, if the CPC is $1, the CTR is 10%, and the expected number of impressions per day is 2,000, then the expected ad spend (EAS) for that day = $1 * 0.1 * 2,000 = $200.

[0084] Thus, if the optimized actual ad spend reported by the search engine is $50, the recovered ad spend is $200 - $50 = $150.

[0085] In some embodiments, method 400 operates with only a single search engine, e.g., the GOOGLE search engine. In such embodiments, method 400 may operate using the data presented in Table 2 below. In other embodiments, comparable data is obtained from other search engines or from search engines in addition to a single major search engine. Results may be aggregated across multiple search engines.

Table 1

[0086] Some of the terms used in Table 2 are defined as follows.

[0087] A traffic source refers to how a visitor arrived at a site, such as by clicking on a paid advertisement, by clicking on an organic listing, etc.

[0088] The number of ad clicks refers to the number of times a user clicks on an advertisement corresponding to the search term being evaluated that is displayed within the SERP returned as a result of a keyword search using the Google search engine.

[0089] Advertising cost: The dollars spent by an advertiser for an advertisement of a paid advertisement that appeared within the SERPs.

[0090] The number of organic clicks refers to the number of times a user clicks on a free "organic" Google search results listing.

[0091] An organic impression refers to the number of times a free listing appears on the SERP in response to a Google search performed by a user.

[0092] The baseline period refers to the period during which no cannibalization actions are performed for a search term, i.e., the period during which the cannibalization score for the search term is not considered in a purchase decision. The baseline period is usually measured in days. These days can be the number of days within a longer time interval, e.g., 4 days out of the past 8 days, or consecutive days.

[0093] Baseline data refers to the data captured during the baseline period.

[0094] Further measures of effectiveness In addition to recovering advertising costs, the effect of reducing spending on cannibalistic advertising can be shown using additional or alternative measures. The following measures, namely, the number of ad clicks, advertising cost, number of organic clicks, impressions, and revenue, can be compared between a period during which no non-cannibalistic action is taken and a similar period during which a non-cannibalistic action is taken. Data can be aggregated across all search terms and over various time intervals (days, weeks, months, etc.).

[0095] Returning to method 400, at step 405, keywords to be evaluated are received or collected. Next, at step 410, for each received keyword, the corresponding cannibalization score generated by method 300 and the performance data described above in Table 2 are collected.

[0096] At step 420, a keyword is selected for processing. At step 430, the expected advertising cost for the keyword is calculated according to Equation 4. Then, at step 440, an optimized advertising cost is obtained from the data collected at step 410. As described above, the optimized advertising cost is typically collected from a search engine.

[0097] At step 450, the recovered advertising cost is calculated according to Equation 3. Also at step 450, as described above, other measures can be calculated, including, inter alia, the number of ad clicks, advertising cost, number of organic clicks, impressions, and revenue. These measures can be calculated or collected for comparable periods with and without non-cannibalistic actions for purposes of comparison.

[0098] At step 460, a determination is made as to whether all keywords have been processed. If not, the process returns to step 420; if so, the process proceeds to step 470.

[0099] In step 470, optionally, the results including the recovered advertising fees are aggregated across all keywords and possibly over multiple time intervals.

[0100] In step 480, the results are provided to a customer or client. The results can be in the form of a file, such as a MICROSOFT EXCEL table, for example, or can be provided as a presentation. Further, such data may constitute intermediate results and may be further analyzed and used for reporting or decision-making purposes.

[0101] FIG. 5 is a block diagram illustrating the software modules of the cannibalistic advertising system (CAS) 100. FIG. 5 illustrates the relevant software elements of the CAS 100, including the client computer 115, the search engine 120, the web server 140, and the advertising server 130.

[0102] The client computer 115 interacts with the user 110 and enables the user 110 to perform a web search using the web browser 118.

[0103] The browser 118 is typically a standard commercially available browser such as MOZILLA FIREFOX or MICROSOFT INTERNET EXPLORER. Alternatively, the browser 118 can also be a client application configured to receive and display graphics, text, multimedia, etc. via the network.

[0104] Browser 118 issues HTTP requests to Internet-connected computers such as search engine 120, web server 140, and client computer 115 and receives HTTP responses. Application server 420 receives the HTTP requests and calls the appropriate advertising server 130 software module to process the requests. Application server 520 can be a commercially available application server that includes a web server that approves and processes the HTTP requests and returns an HTTP response along with optional data content that can be a web page such as an HTML document and linked objects (such as images).

[0105] Application server 520 establishes and manages sessions with search engine 120 and web server 140. Further, application server 520 can interact with client computer 115.

[0106] The software modules of search engine 120 are generally outside the scope of the present invention. However, as described above and detailed in Table 2, the search engine is expected to provide various result data related to advertisements purchased by advertisers, and the search engine provides that various result data within the SERP in response to a search. Web server 140 manages one or more websites 145 where each website includes one or more domains.

[0107] Advertising server 130 includes a keyword collector 530, a rule definer 532, a co - eating advertisement (CA) analyzer 135, a co - eating advertisement (CA) report generator 534, and in some embodiments, an advertisement purchaser 536, a recovered advertisement analyzer, a keyword database 550, a rule database 552, and an advertisement database 554. It should be understood that each of the above - mentioned databases may be implemented as one or more computer files spanning one or more physical storage mechanisms. In one embodiment, each of the above - mentioned databases is implemented as one or more relational databases and is accessed using structured query language (SQL).

[0108] The keyword collector 530 obtains keywords from the search engine 120 and possibly from other sources. The keyword collector 530 may also obtain keywords from advertisers, for example, keywords within a computer file supplied by the advertiser. The keyword collector 530 stores the keywords in the keyword database 450. The keyword collector 530 performs the processing related to step 305 of method 300.

[0109] The keyword collector 530 further collects from the search engine 120 the data required by method 400 for calculating the recovered advertising costs including the revenue, average click - per - cost (CPC), average click - through rate (CTR), and impressions resulting from the keywords.

[0110] The rule definer 532 defines rules for determining scores for advertisements within the SERP. The rule definer 532 stores the rules in the rule database 552. The rule definer 532 implements step 310 of method 300. The rule definer 532 can be implemented in various ways. For example, in some embodiments, the rule definer 532 simply receives a text file defining the rules, while in other embodiments, the rule definer 532 provides a graphical interface to the client computer 115 that enables a user to interactively define the rules. Generally, the method for defining the rules is outside the scope of the present invention.

[0111] The CA analyzer 135 executes the processing related to steps 315 - 340 of method 300. The CA analyzer 135 uses the collected keywords stored in the keyword database 550 to obtain SERPs, identify the positions of paid advertisements and corresponding listings, and store the results in the keyword database 550. The CA analyzer 135 further evaluates the SERPs to generate a cannibalization advertisement score and stores the results in the advertisement database 554.

[0112] The CA report generator 534 generates a report providing the cannibalization advertisement score for the advertisements. The CA report generator 534 executes step 345 of method 300.

[0113] In some embodiments, the advertisement purchaser 536 purchases advertisements from the search engine 120 taking into account the results of the cannibalization advertisement analysis represented by the cannibalization advertisement report stored in the advertisement database 554. Specifically, the advertisement purchaser 536 determines on a case - by - case basis whether to purchase an advertisement based on its cannibalization score. In other embodiments, the advertisement purchaser 536 is not part of the CAS 100. For example, the functionality of the advertisement purchaser 536 can be performed by a third - party advertising agency.

[0114] The Recovered Ad Spend Analyzer (RAS Analyzer) 538 analyzes the results, i.e., the effects, obtained by not purchasing ads considered cannibalistic. Generally, the RAS Analyzer 538 executes method 400 to generate reports or other results that can be provided to advertisers. The RAS Analyzer 538 can also calculate other metrics of effects other than recovered ad spend, as described above. Such metrics include, among others, the number of ad clicks, ad cost, number of organic clicks, impressions, and revenue during comparable periods with and without non-cannibalistic actions. The RAS Analyzer 538 stores the results in the ad database 554.

[0115] The keyword database 550 stores the collected keywords. The keyword database 550 also stores the position or average position of the ads and the corresponding free listings, where the ads are published by the advertiser, or by the ad server 130, or by another party acting on behalf of the advertiser, and the ads appear within the SERPs returned as a result of a keyword search.

[0116] The rule database 552 stores the rules used to generate the cannibalization scores for the ads.

[0117] The ad database 554 stores the ads supplied by the advertisers corresponding to the collected keywords. Generally, each keyword of interest to the advertiser has a corresponding paid ad that can be published by the search engine. The ad database 554 also stores the CA reports generated by the CA report generator 534 and the recovered ad spend and other result data generated by the RAS Analyzer 538.

[0118] The above specifications, examples, and data provide a complete description of the manufacture and use of the compositions of the present invention. Many embodiments of the present invention can be made without departing from the spirit and scope of the present invention.

[0119]

Table 2

Claims

**Claim 1** A computer-implemented method for adjusting bids for Internet advertisements in an Internet advertising campaign, comprising: a keyword collector collecting a plurality of keywords and a plurality of advertisements related to a specified advertiser, each keyword corresponding to one of the plurality of advertisements that the advertiser intends to purchase as part of an Internet advertising campaign, and in response to receiving a keyword, a search engine returning a search engine results page (SERP), the SERP including (1) at least one advertisement and (2) at least one free listing, the advertisement having an advertisement position within the SERP related to other advertisements, the position of the first advertisement being the most valuable position, and the value decreasing as the ordinal number of the advertisement position increases, and (2) at least one free listing, each free listing including a link to a landing page, the free listing having a free listing position within the SERP, the position of the first advertisement being the most valuable position, and the value decreasing as the ordinal number of the advertisement position increases, and at least one free listing; a cannibalization rule definer maintaining at least one cannibalization rule for calculating a cannibalization score for an advertisement, the cannibalization score for the advertisement indicating that the advertisement is cannibalized when it generates a reduced value for the advertisement due to the position of the advertisement within the SERP and the listing position of the corresponding free listing within the same SERP, the corresponding free listing referring to the same product or service as that referred to by the advertisement; a cannibalization advertisement analyzer periodically determining whether to purchase a specified advertisement from among the plurality of received advertisements, the periodic determination comprising: performing a keyword search to obtain a SERP for the keyword corresponding to the specified advertisement; identifying the advertisement position of the specified advertisement within the SERP and the corresponding free listing within the SERP; generating a cannibalization score for the specified advertisement by applying the at least one cannibalization rule to the specified advertisement; The step in which the advertisement purchaser executes the purchase of the advertisements for the plurality of collected advertisements, wherein when the collected cannibalization score for an advertisement indicates that the advertisement is a cannibalization advertisement, the advertisement is not purchased, and A computer-implemented method including the above. **Claim 2**: The method according to claim 1, wherein the cannibalization score represents a measure selected from the group consisting of an estimated value of a decrease in revenue for the advertiser due to the advertisement appearing in the same SERP as the corresponding listing, an estimated value of the likelihood that the advertisement is a cannibalization advertisement, or a BOOLEAN value indicating whether the advertisement is a cannibalization advertisement. **Claim 3**: The method according to claim 1 or 2, wherein the cannibalization score indicates that the advertisement is a cannibalization advertisement when the advertisement appears in the position of the first advertisement in the SERP, there is no advertisement in the position of the second advertisement, and the corresponding free listing appears in the position of the first free listing in the SERP. **Claim 4**: The method according to claim 1, wherein at least one cannibalization rule is additionally based on one or more factors selected from the group consisting of the number of advertisements in the SERP, the average revenue per click for the advertisement, and the average revenue per click for the free listing. **Claim 5** A category selected from the group consisting of an advertisement posted by the designated advertiser, a friendly advertisement, a competing advertisement, or another advertisement can be assigned to each advertisement in the SERP, and at least one rule is based on the category of the advertisement in the SERP. The method according to claim 1. **Claim 6** The distance between the advertisement and the free listing in the SERP can be calculated, and at least one cannibalization rule is based on the distance between the advertisement posted by the advertiser and the corresponding free listing. The method according to claim 1. **Claim 7**: The method according to claim 1, further including the step of generating a report including the cannibalization score for each advertisement that the advertiser intends to purchase. Claim 8. A keyword collector for collecting a plurality of keywords and a plurality of advertisements, wherein each keyword corresponds to one of the plurality of advertisements that an advertiser intends to purchase as part of an Internet advertising campaign, and in response to receiving a keyword, a search engine returns a search engine results page (SERP), the SERP including: (1) one or more advertisements, and (2) at least one free listing, wherein the advertisements have positions of the advertisements within the SERP related to other advertisements, the position of the first advertisement being the most valuable position, and the value decreasing as the ordinal number of the position of the advertisement increases; and (2) at least one free listing, wherein each free listing includes a link to a landing page, the free listings have positions of the free listings within the SERP, the position of the first advertisement being the most valuable position, and the value decreasing as the ordinal number of the position of the advertisement increases, and a keyword collector including at least one free listing. A rule database for maintaining at least one cannibalization rule for calculating a cannibalization score for an advertisement, wherein the cannibalization score for the advertisement indicates that the advertisement is cannibalization when it generates a reduced value for the advertisement due to the position of the advertisement within the SERP and the listing position corresponding to the free listing within the same SERP, and the corresponding free listing refers to the same product or service as that referred to by the advertisement, and a keyword definer. A CA analyzer for periodically determining whether to purchase a specified advertisement from among the plurality of received advertisements, the periodic determination including: Executing a keyword search to obtain a SERP for the keyword corresponding to the specified advertisement. Identifying the position of the specified advertisement within the SERP and the position of the corresponding free listing within the SERP. Generating a cannibalization score for the specified advertisement by applying the at least one cannibalization rule to the specified advertisement. Executing a step of purchasing the advertisement for the plurality of collected advertisements, wherein the advertisement is not purchased when the collected cannibalization score for the advertisement indicates that the advertisement is cannibalization. And a CA analyzer including the steps. A network computing device comprising

9. The network computing device according to claim 8, wherein at least one cannibalization rule is additionally based on one or more factors selected from the group consisting of the number of advertisements in the SERP, the position of the corresponding free listing in the SERP, the average revenue per click for the advertisement, and the average revenue per click for the free listing.

10.

10. A category selected from the group consisting of an advertisement posted by the designated advertiser, a friendly advertisement, a competing advertisement, or another advertisement can be assigned to each advertisement in the SERP, and at least one rule is based on the category of the advertisement in the SERP. The network computing device according to claim 8.

11.

11. The distance between an advertisement and a free listing in the SERP can be calculated, and at least one cannibalization rule is based on the distance between the advertisement posted by the designated advertiser and the corresponding free listing. The network computing device according to claim 8.

12. The network computing device according to claim 8, further comprising a cannibalization advertisement report generator that generates a report including a cannibalization score for each advertisement that the advertiser intends to purchase.

13.

13. The network computing device according to claim 12, further comprising an advertisement purchaser that purchases an advertisement from the search engine at least partially based on the report of the cannibalization advertisement.

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