Patent Abstract:
Local businesses using on line search advertising to attract customers have a difficult time determining the effectiveness of various search terms or how much to bid for each term or search phrase. Local businesses typically fall into a national category. This national category has words and terms related to it which consumers and businesses use to search for providers and information within the category. Multivariate analysis can be used across target words and terms, negative words and terms, product profit margin, product sales volume, customer value, and click thru success to determine an index value for each search term. This analysis can be used to determine the best potential ad budget for a paid search campaign and the best phrases to deploy and optimal bid rates.

Full Description:
FIELD OF THE INVENTION 
       [0001]    This disclosure relates to the field of on line paid search advertising and more particularly to a methodology for paid search ad agencies servicing local businesses to determine which of the possible thousands of paid search terms and words provide the best ad spend return for the business they are servicing and the appropriate amount of ad spend to capture the particular local market they are servicing. 
       BACKGROUND 
       [0002]    Online search powered by Web-based search engines has proven to be one of the most common methods used by consumers and businesses to find and purchase both products and services. Online search providers such as Google, Bing, and Yahoo! now have the ability for a local business to purchase search based ad content that only pertains to the local businesses geographic location. 
         [0003]    The economy is made up of millions of local businesses who are potential purchasers of local search based ad content. These local businesses have established web sites to promote the products and/or services they provide to the local community. Online paid search advertising is on a path to quickly surpass previous forms of advertising local businesses used to reach potential clients such as phone book advertising. The online search providers have employed a system to sell their search based advertising which at first seems quite simple for a local business to deploy and purchase. However, local businesses do not typically have the ability to analyze all of the thousands of possible search terms and phrases to develop an effective local paid search ad campaign. Difficulties include determining how to establish a correct budget for the desired results, how to analyze changing local paid search trends, and how to determine which terms and words actually provide a return on their advertising investment. However on a national level, these local businesses typically fall into a certain category. Local businesses all across the country in this category share common terms and phrases related to their specific business. Local businesses also share several types of customer groups who represent different levels of profit and ongoing profit potential for the local business. Online search providers provide back to the paid advertiser a great deal of data. Never before in the history of advertising has there been such a large amount of raw data available to the individual business related to their paid search advertising campaign. This data comes from both the analytic tools the local business may place on their website and the providers of paid search advertising. However the ability to properly analyze this data is beyond the reach of the local business owner. Local business owners typically make a guess on several things including key search terms, negative search terms, and ad budget. Local business owners do not have a method to take the data fed back to them from the results of their self run campaign to properly analyze the results. A need exists to provide local business owners with a mathematical strategy to develop a paid local search based advertising campaign. 
       SUMMARY 
       [0004]    In one aspect, a method and system disclosed herein includes gathering data pertaining to a national category of business and in addition data received from on line search providers, calculating the value of at least in part on terms, words, phrases to the local business owner to develop a target budget and key word campaign for a local paid search campaign across any number of online search ad providers. 
         [0005]    A local business owner wishing to embark on a paid search advertising campaign has one of two choices: i) attempt to design and run the campaign themselves or ii) pay an outside agency to run the campaign. The local business owner may know his field better than an outside agency. An outside agency may have a better understanding of paid search advertising due to trial and error experience. 
         [0006]    A method to categorize the local business owner into a national vertical segment will reveal words, terms, and phrases consumers and businesses use to seek out providers of this vertical segment. High value target terms, words and phrases will be established through methods including data analysis and interviews with other local business owners at a national level in the same vertical segment. For example a potential local customer searching for the term Lexus is quite valuable to the local business selling the Lexus brand, but has very little value to the local business selling appliances. However for the local business selling a competing brand such as BMW, the Lexus search term would have a high value. Furthermore, a local business engaged in repair of the Lexus brand would consider the search term “Lexus repair” to have a very high long term value in capturing a potential repeat customer. 
         [0007]    Certain categories of products sold by local businesses have a higher profit margin than other products sold by the same local business. These categories of products have words, terms, and phrases associated with them. For example, a local audio/video business may engage in selling expensive high profit home theater systems and also engage in selling low margin, low priced televisions. A search term such as “best home theater system” has a higher value to the local audio/video business than the search term of “televisions”. Furthermore, the search term of “cheap televisions” may have no value at all to the local audio/video business and a negative term may be employed in the paid search terms to prevent any type of ad for their business being presented to a customer searching for “cheap televisions.” 
         [0008]    Furthermore, some search words, terms, or phrases may be very specific to the local business in a category, yet are not widely searched terms. An example of this may be a search term such as “best Maserati dealer in Utah”. This combination of search terms may have a very low cost to allow the ad to be displayed across paid search providers, but this potential client would have a high value to the Maserati dealer in Utah. 
         [0009]    All of the potential paid search words, terms, and phrases, including negative phrases which prevent an ad from showing can be captured in a relational database that links to the specific national business category the local business exists within. A weighted index number can then be assigned to each potential word, term, or phrase used in a paid search ad based upon the national category the local business falls within. 
         [0010]    Data from the providers of paid search advertising such as Google, Bing, Yahoo!, and others will reveal the estimated market price for high positioning of paid search ads based upon the various geographic locations. High positioning of paid search ads is desired by the local business to present their ad to potential clients searching for providers of their product or service. Furthermore data from the paid search providers will reveal the inventory of search ads available in a specific local geographic area. Both of these data sets are changing every minute and can be constantly updated with real time information. 
         [0011]    Data from the providers of paid search advertising such as Google, Bing, Yahoo!, and others is available in real time to measure the effectiveness of both paid search words, terms, and phrases and the positioning of these words, terms, and phrases based both on the local ad being shown to the local potential customer and the rate of clicks to the promoting website of the local business by the potential local customer. 
         [0012]    Multivariate analysis can be used across a set of relational data bases to establish the target budget for the local business falling into a national category, based upon their geographic location, and the national category. On going updates to the data bases, from the providers of the local paid search ads can be fed back into the data bases as related to providing enough ad spend for the ad to be shown, positioning of ads, and click through rates of the ad to the local businesses web site. This analysis can then adjust the ad spend budget and words, terms, phrases and keyword bid rates based on real time local data that relates to the local business. Data trends can be found on a national level as they relate to search words, terms, and phrases as the market within the national category may evolve. 
     
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
         [0013]    The invention and the following detailed description may be understood by reference to the following figures: 
           [0014]      FIG. 1  illustrates a generalized method to establish a vertical master list. 
           [0015]      FIG. 2  illustrates a method to establish a set of negative terms for a vertical master list. 
           [0016]      FIG. 3  illustrates a generalized method to develop a connected set of key words, terms, and phrases with related negative key words, terms, and phrases (word groupings). 
           [0017]      FIG. 4  illustrates a generalized method to place a value in several categories on each word grouping. 
           [0018]      FIG. 5  illustrates a mathematical method to derive an index value for each word grouping. 
           [0019]      FIG. 6  illustrates a method to project a local cost for a preferred ad position for each word grouping. 
           [0020]      FIG. 7  illustrates a generalized method to add local specific word groupings and use a mathematical method to obtain an index factor for the local specific word groupings. 
           [0021]      FIG. 8  illustrates a mathematical method to derive a total suggested budget for a local individual business search based ad campaign. 
           [0022]      FIG. 9  illustrates a generalized process to obtain an actual budget from an individual local business and from there to use a mathematical method to derive a target word grouping and target bid price for each word grouping. 
           [0023]      FIG. 10  illustrates a method to analyze real time results of the individual local business ad campaign and feed these results into a mathematical method to obtain a local index score for word groupings, which through a mathematical method derives a revised target word grouping and revised target paid search campaign budget. 
       
    
    
     DETAILED DESCRIPTION 
       [0024]    The methods and systems disclosed herein relate to the domain of paid local on line search campaigns for local businesses. 
         [0025]      FIG. 1  represents a method  100  to derive a list of terms and phrases  104  that relate to a specific category of business  101 . The method  100  is a manual interview process  102  with person or persons having detailed knowledge of the specific category of business  101 . The specific category of business  101  may be any type of business where there may be other businesses in this same category across a large geographic region. The interview process  102  generates a list of terms and phrases which are refined by a data analysis method  103  to construct a vertical master list  104  of terms and phrases related to a specific national business category  101 . The method  100  may be applied to any category of business. In embodiments, the vertical master will be all terms and phrases that could be used in a search that could be associated with products and services related to the specific category of business. Terms and phrases that could possibly not be related to the specific business will be removed through the data analysis method. 
         [0026]      FIG. 2  represents a method  109  to derive a list of negative terms and phrases  105 . A term or phrase found in the vertical master list  104  when input into a search engine in combination with a term or phrase not found in the vertical master list  104  may result in an undesirable search result. The search engines  107  such as Google, Bing, Yahoo!, and others provide a set of tools  106  used to determine other terms and phrases related to a searched term or phrase  104 . These other terms and phrases may have a negative impact on the desired outcome of a paid search within a local business paid search campaign  147 . These undesired other terms and phrases are input into the vertical master negative terms list  108 . In embodiments, the negative terms and phrases may be obtained by a manual method of entering each of the terms and phrases in the vertical master list  104  and comparing them to the existing terms and phrases in the vertical master list or an automated data query method of the search engines. 
         [0027]      FIG. 3  represents a method  109  to derive a list of keyword terms and phrases in addition to a list of relevant negative terms and phrases  111 . The method  109  is a manual interview process  110  with person or persons having detailed knowledge of the specific category of business  101 . The interview and analysis method  110  will confirm or deny with person or persons having detailed knowledge of the specific business category  101  that the negative terms and phrases  108  derived with search engine  107  tools  106  are an accurate data set. The interview and analysis  110  generates a list of keyword terms and phrases in addition to a list of relevant negative terms and phrases  111 . In embodiments, this method  109  involves comparing with the specific industry expert or experts every related term or phrase derived from the method in  FIG. 2  that could be a possible negative term of phrase. A negative term or phrase when entered into a search engine with a desired term or phrase could yield a search result not relevant to the specific business category. In embodiments, the negative terms and phrases will be used in conjunction with the desired terms and phrases in an ad campaign for individual businesses in the specific national business category. These negative terms and phrases will prevent on line ads from being displayed if the negative term or phrase was entered by the party entering data into a search engine. 
         [0028]      FIG. 4  represents a method  112  to add related data to the keyword terms and phrases  111 . A relational database  118  is built which links each individual term or phrase  113  to factors that influence the value of the individual term or phrase  113 . The interview and analysis process  110  includes several questions about each individual term or phrase  113 . The answers to these questions are typically obvious to someone with experience in the individual business category. Related product margin  114  refers to the profit percent typical of products or services shown when an on line search is done for that individual word or term  113 . Related selling price  115  refers to the total dollar selling price typical of products or services shown when an on line search is done for that individual word or term  113 . Related customer value  116  refers to a scale of long term potential value of a person or persons typically searching for the individual word or term  113 . Other relationships  117  may exist for the individual search word or term and may include but not be limited to relevant industry news about the individual search word or term  113 , reputation of any products or services linked to the individual search term or phrase  113 , and data search trends of the individual search word or term  113 . The method  112  results in a large database of information linked to each individual search word or term. An example of one row of the database  118  is shown in  FIG. 4 . All fields in the database  118  with the exception of the individual word or term  113  are assigned a statistical value. In embodiments, the related profit margin, related selling price, related customer value, and other attributes are used to assign values to each of the search terms and phrases. In embodiments, these values may vary from one specific national business to another. In embodiments, these values are assigned through a series of interviews with experts or experts related to the specific national business category. 
         [0029]      FIG. 5  represents a mathematical method  119  using multivariate analysis to derive an index factor  125  for each individual search term or phrase  113 . The weighting factor  120  for related profit margin  114  is assigned the same statistical value across the database for the individual national business in the same category  FIG. 1   101 . The weighting factor  121  for related selling price  115  is assigned the same statistical value across the database for the individual national business in the same category  FIG. 1   101 . The weighting factor  122  for related customer value  116  is assigned the same statistical value across the database for the individual national business in the same category  FIG. 1   101 . The other weighting factors  123  for other related values  117  are each assigned the same statistical value across the database for the individual national business in the same category  FIG. 4   101 . The statistical values assigned to each weighting factor will vary from individual national business  FIG. 4   101 . to another. Using multivariate analysis  124 , an index factor  125  is calculated for each individual search term or phrase in the relational database  FIG. 4   118  for the individual category of business  FIG. 4   101 . In embodiments, this statistical method weighs the various characteristics of the search terms and phrases to derive a true value of the search term or phrase as it relates to other possible search terms and phrases of the same specific national business category. 
         [0030]      FIG. 6  represents a method  126  to project a local target cost for preferred ad position  128  for each individual search term or phrase in a specific geographic area. Bid rates for the same individual search term or phrase vary widely across geographic regions. Using the local analysis tools  127  provided by the national search engines  107 , a projected cost for preferred ad position  128  can be derived for each individual search term or phrase  113 . The projected cost for preferred ad position  128  for each individual search term or phrase  113  populates a field in the relational database  FIG. 4   118 . In embodiments, a manual or automated tool may be used to enter each of the various search terms and phrases along with the related negative terms and phrases into the advertising tools provided by national search engines to derive the estimated local cost, specific to each geographic region, of having the national search engines display an ad related to these search terms and phrases in a preferred position. 
         [0031]      FIG. 7  represents a method to derive a specific list of search terms and phrases for an individual business from the national specific business category the individual local business falls within and to add local specific search terms  133  or phrases to a database for each individual local business  130  and to derive using multivariate analysis  124  an index factor  125  for each of the local individual business specific search terms and phrases  133  and to derive a projected target cost for preferred placement for each of the individual local business terms and phrases. Using a business process  131 , each individual local business  130  is interviewed. All of the national search terms and phrases  134  are discussed with the individual local business. Not all of these national terms and phrases will be relevant to the individual local business  130  due to many factors including product line differences within the same category and or the fact the individual local business may not specialize in all areas of this specific national business. The business process  131  will eliminate for the specific individual local business  130  any of the national terms and phrases  134  that are not relevant to the individual local business  130 . This data set becomes the individual local business target word list  132 . During the business process  131  certain local specific search words and phrases  133  may be derived. These local specific terms and phrases  133  may be geographic terms and phrases, local slang or colloquialisms, terms and phrases related to unique products or services the individual local business provides, or any other terms and phrases uniquely linked to the individual local business. This data set of unique local terms and phrases  133  is processed with the same method used in  FIG. 4   112  to add related data to terms and phrases related to the individual local business. Using the same mathematical method shown in  FIG. 5   119 , a weighting factor is assigned to each of the related terms including profit margin  114 , selling price  115 , customer value  116 , and other relationships  117 . Using multivariate analysis  124  an index factor  125  is assigned to each individual term or phrase in the local individual business specific terms and phrase database  133 . Using the same method represented in  FIG. 6   126 , each of the local individual business specific terms and phrases  133  is assigned a projected cost for preferred ad position  128 . In embodiments, this method is used to possibly reduce the size of the list of all terms and phrases for a specific national industry to only those terms and phrases that relate to the products and or services provided by the specific local business. In embodiments, the interview method is used to derive any other terms and phrases that may relate specifically to the individual business. In embodiments, this statistical method weighs the various characteristics of the specific search terms and phrases related to the individual business to derive a true value of the search term or phrase as it relates to other possible search terms and phrases of the same specific national business category. In embodiments, a manual or automated tool may be used to enter each of the local specific to the individual business search terms and phrases along with the related negative terms and phrases into the advertising tools provided by national search engines to derive the estimated local cost, specific to the geographic region of the local business, of having the national search engines display an ad related to these search terms and phrases in a preferred position. 
         [0032]      FIG. 8  represents a method  135  to derive a suggested advertising budget for paid local search  138  using multivariate analysis  139  for a specific individual local business  FIG. 7   130 . The method applies multivariate analysis  139  to the refined national terms and phrase list  132 , the individual local business specific terms and phrase list  136 , the index factor  137  derived by the method represented in  FIG. 5   119 , and the projected target cost for preferred ad position  128  for each of the terms and words in both the refined national terms and phrase target list  132  and the individual local business specific terms and phrase list  136 . The analysis produces a suggested ad spend budget  138  for the individual local business. In embodiments, this is a method to derive, an estimated search engine advertising ad budget for a specific local business. In embodiments, the terms and phrases from the national list that relate to the specific local business, the terms and phrases that relate only to the specific local business, the estimated cost of displaying these search terms in preferred position, and the relative importance of each of these terms and phrases are all entered into a multivariate analysis tool to derive the total estimated advertising budget needed for the specific local business. 
         [0033]      FIG. 9  represents a business process  140  to refine an on line search ad spend budget for an individual local business  130 . Using this refined budget, multivariate analysis  143  is applied to find the target word group list  144  and target bid price  145  for each of these individual terms and phrases  132 ,  136 . The suggested ad spend budget derived using the method  135  described in  FIG. 8  may or may not exceed the ad spending ability of the individual local business. A budget business process  141  with the individual local business  130  will determine an on line ad spend budget  142  that fits the current spending ability of the individual local business. Using multivariate analysis  143  on the individual local business target word group list derived from national list  132 , the individual local business unique local target word group list  136 , the index factor for each word group in each target list  137 , and the local projected cost for preferred ad position  128  for each word group in each target list derives a list of target terms and phrases  144  and a suggested bid price for preferred ad position  145  for each of these suggested terms and phrases  144  that match the ad spend budget  142  of the individual local business  130 . In embodiments, the method derives an optimal set of search terms and phrases for the individual local small business to place paid search bids on that will match the small business budget needs. In many cases, most businesses will not be able to spend up to the recommended spend level for optimum placement for all of the possible search terms and phrases that relate to their specific category of business. In embodiments, a business interview process with the local business determines a budget for the local business. The need exists to determine which search terms and phrases related to the individual business would generate the largest pool of potential profitable customers. In embodiments, the method uses multivariate analysis to derive the list of search terms and phrases while also establishing a suggested bid price where the combination of search terms and phrases coupled with the suggested bid price should closely match the budget determined in the interview process. In embodiments, the interview business process occurs on a daily, weekly, monthly, or other seasonal time frame and can be used to derive a new set of search terms and phrases with their suggested bid price at any time. 
         [0034]      FIG. 10  represents a method  162  to continually refine the target word group list  159  for the individual local business  FIG. 8   130  and the target price for preferred ad placement  160  of the target word group list. An individual local business  FIG. 8   130  will run a paid search campaign  147  with one or more paid search providers. These paid search providers generate detailed data results  149  related to the success of the paid search campaign of the individual local business. This data may consist of total impressions for each individual search term or phrase  151 , total clicks on each individual ad for each individual search term or phrase  152 , average cost per ad click  153 , positioning of the individual ad  154 , a score from the paid search provider on the individual ad  155 , and other related data  156 . The individual local business will have a website  146  the ad clicks are directed to. The website will have tools  161  embedded in the website to track many details related to clicks to the website including but not limited to, time spent on the web site, pages visited on the web site, geographic location of the user clicking on the ad and more. Both the data from the paid search providers related to the individual local business paid search campaign and the data from the individual local business website are entered into a relational database. Based on this data, multivariate analysis  157  is used to obtain an additional index value known as the local index value  158 . This is an individual value for each of the search terms and phrases of the individual local business paid search campaign. Using the additional index value  158  and multivariate analysis  157  a refined suggested ad budget  160  is calculated and in addition a refined list of search terms and phrases  159  suggested for the individual local business. In embodiments, this method uses all of the data available to the individual business to refine the advertising campaign based on multivariate analysis. In embodiments, the method described may or may not run in real time, daily, weekly, monthly or any other cycle. In embodiments, this method may be used to provide the individual local business with recommended paid on line search budgets based upon changing conditions. 
         [0035]    In embodiments, the methods of this invention use national business category experts, multivariate analysis, and individual local specific business interviews to derive an optimum on line paid search advertising campaign for a specific local business. In embodiments, the data provided by both the national search engines and the individual local business web site are used with multivariate analysis to refine the on line paid search ad campaign of the individual local business.

Technology Classification (CPC): 6