Methods for Cross-Market Brand Advertising, Content Metric Analysis, and Placement Recommendations

Abstract

A computer-implemented method for processing and optimizing selection of placement of advertising content related to a brand in websites is provided. The method includes receiving from the user, attributes of an advertisement to be placed on a brand-centric website that relates to the brand, and receiving selections for types of websites to place the advertisement. The method further includes obtaining metrics from selected websites and historical performance for similar advertisements when placed on the selected websites. The method includes processing the obtained metrics and historical performance to define an advertising model. The advertising model defines a score correlated to effectiveness of the advertisement. Optimizing the advertising model is then performed to define a recommended advertising model, where the recommended advertising model defines optimal selections of websites for placement of the advertisement. The optimizing uses multivariable optimization to correlate the obtained metrics to a desired optimization criteria.

What is claimed is: 
     
         1 . A method comprising:
 receiving attributes of an advertisement to be placed on one of a plurality of brand-centric websites, the brand-centric websites focused on a brand;   presenting the brand-centric websites to a remote computer based on the attributes;   receiving a selection of the one of the brand-centric websites from the remote computer;   analyzing the one of the brand-centric websites to search a computer network to generate suggestions of content-related websites in which an advertisement is to be placed, wherein the content-related websites in which the advertisement is to be placed has less information regarding the brand than that in the one of the brand-centric websites in which the advertisement is to be placed, wherein data for generating content of the one of the brand-centric websites and the content-related websites is obtained by a harvester, wherein a data type processor is configured to classify the data into video, audio, and text to generate classified data, wherein the classified data is stored in an entertainment content repository, wherein the content-related websites request the classified data via corresponding application programming interfaces from the content repository;   receiving a selection of one or more of the content-related websites from the remote computer;   obtaining metrics for similar advertisements when placed on a plurality of selected websites, the selected websites including the one of the brand-centric websites and the one or more of the content-related websites;   processing the metrics to define an advertising model, the advertising model having a score correlated to effectiveness of the advertisement; and   optimizing the advertising model to define a recommended advertising model, the recommended advertising model defining optimal suggestions of websites including the one of the brand-centric websites that has the classified data obtained from the entertainment content repository and in which the advertisement is to be placed.   
     
     
         2 . The method of  claim 1 , wherein the optimizing of the advertising model includes executing multivariable optimization to enable emphasis or non-emphasis of selection criteria. 
     
     
         3 . The method of  claim 1 , wherein the attributes include a type of product or service to be advertised, or a marketing budget of an advertiser, or a type of the advertisement, or a target customer of the advertisement, or a combination of two or more thereof. 
     
     
         4 . The method of  claim 1 , wherein the harvester is configured to obtain the data for generating the content from a plurality of third-party data feeds, wherein the third-party data feeds have information about a movie regarding the brand or a game regarding the brand or a television show regarding the brand or a combination of two or more thereof. 
     
     
         5 . The method of  claim 1 , further comprising:
 monitoring user interaction of a plurality of users with one or more modules of the one of the brand-centric websites;   accessing a plurality of profiles of the plurality of users interacting with the one or more modules;   suggesting changes to the one or more modules based on the user interaction and the profiles of the plurality of users.   
     
     
         6 . The method of  claim 1 , the method further comprising:
 monitoring user interaction of a plurality of users with one or more modules on the one of the brand-centric websites;   accessing a plurality of profiles of the plurality of users interacting with the one or more modules;   allowing access to information regarding the user interaction and the user profiles to a producer of the one of the brand-centric websites;   receiving modifications to the one or more modules regarding the brand from the producer of the one of the brand-centric websites.   
     
     
         7 . The method of  claim 1 , wherein the metrics include revenues generated by placing the similar advertisements on the selected websites, or demographics of a plurality of users accessing the selected websites, or a number of clicks of the similar advertisements placed on the selected websites, or sales of products or services from the similar advertisements placed on the selected websites, or a combination of two or more thereof. 
     
     
         8 . The method of  claim 1 , wherein the similar advertisements advertise the brand. 
     
     
         9 . The method of  claim 1 , wherein said processing the metrics is performed to determine a demographic of users interested in purchasing a product or service advertised by the advertisement. 
     
     
         10 . A system comprising:
 an ad processing server in communication with a remote computer configured to be accessed by an advertiser, the ad processing server configured to receive attributes from the remote computer of an advertisement to be placed in one of a plurality of brand-centric websites, wherein the ad processing server is configured to provide the brand-centric websites to the remote computer based on the attributes, wherein the ad processing server is configured to receive a selection of the one of the brand-centric websites from the remote computer, wherein the ad processing server is configured to analyze the one of the brand-centric websites to search a computer network to generate suggestions of content-related websites in which the advertisement is to be placed, wherein the content-related websites in which the advertisement is to be placed has less information regarding a brand than that in the one of the brand-centric websites in which the advertisement is to be placed;   a harvester coupled to the ad processing server, wherein the harvester is configured to obtain data for generating content of the one of the brand-centric websites and the content-related websites;   a data type processor coupled to the harvester, wherein the data type processor is configured to classify the data into video, audio, and text to generate classified data;   a content repository coupled to the data type processor, wherein the content repository is configured to store the classified data,   wherein the content-related websites request the classified data via corresponding application programming interfaces from the content repository,   a metrics server coupled to the ad processing server, wherein the metrics server is configured to receive a selection of the one or more of the content-related websites, wherein the metrics server is configured to process metrics for similar advertisements when placed on a plurality of selected websites, wherein the selected websites include the one of the brand-centric websites and the one or more of the content-related websites, wherein the metrics server is configured to process the metrics to define an advertising model, wherein the advertising model has a score correlated to effectiveness of the advertisement; and   an optimization engine coupled to the metrics server, wherein the optimization engine is configured to optimize the advertising model to define a recommended advertising model, wherein the recommended advertising model defines optimal suggestions of websites including the one of the brand-centric websites that has the classified data obtained from the entertainment content repository and in which the advertisement is to be placed.   
     
     
         11 . The system of  claim 10 , wherein the advertising model is optimized by performed multivariable optimization to enable emphasis or non-emphasis of selection criteria. 
     
     
         12 . The system of  claim 10 , wherein the attributes include a type of product or service to be advertised, or a marketing budget of an advertiser, or a type of the advertisement, or a target customer of the advertisement, or a combination of two or more thereof. 
     
     
         13 . The system of  claim 10 , wherein the harvester is configured to obtain the data for generating the content from a plurality of third-party data feeds, wherein the third-party data feeds have information about a movie regarding the brand or a game regarding the brand or a television show regarding the brand or a combination of two or more thereof. 
     
     
         14 . The system of  claim 10 , further comprising:
 a monitoring processor coupled to the metrics server, wherein the monitoring processor is configured to monitor user interaction of a plurality of users with one or more modules of the one of the brand-centric websites;   a user profile processor coupled to the metrics server, wherein the user profile processor is configured to access a plurality of profiles of the plurality of users interacting with the one or more modules;   a suggestion processor coupled to the monitoring processor and the user profile processor, wherein the suggestion processor is configured to suggest changes to the one or more modules based on the user interaction and the profiles of the plurality of users.   
     
     
         15 . The system of  claim 10 , further comprising:
 a monitoring processor coupled to the metrics server, wherein the monitoring processor is configured to monitor user interaction of a plurality of users with one or more modules on the one of the brand-centric websites;   a user profile processor coupled to the metrics server, wherein the user profile processor is configured to access a plurality of profiles of the plurality of users interacting with the one or more modules,   wherein the content repository is configured to store information regarding the user interaction and the profiles, wherein access to the information regarding the user interaction and the user profiles is provided to a producer remote computer that is configured to be accessed by a producer of the one of the brand-centric websites,   a modification processor coupled to the producer remote computer, wherein the modification processor is configured to receive from the producer remote computer changes regarding the brand to be made to the one of the brand-centric websites.   
     
     
         16 . The system of  claim 10 , wherein the metrics include revenues generated by placing the similar advertisements on the selected websites, or demographics of a plurality of users accessing the selected websites, or a number of clicks of the similar advertisements placed on the selected websites, or sales of products or services from the similar advertisements placed on the selected websites, or a combination of two or more thereof. 
     
     
         17 . The system of  claim 10 , wherein the similar advertisements advertise the brand. 
     
     
         18 . The system of  claim 10 , wherein the metrics server is configured to process the metrics for the similar advertisements to determine a demographic of users interested in purchasing a product or service advertised by the advertisement. 
     
     
         19 . A computer readable medium containing program instructions, wherein execution of the program instructions by one or more processors of a computer system causes the one or more processors to execute a plurality of operations of:
 receiving attributes of an advertisement to be placed on one of a plurality of brand-centric websites, the brand-centric websites focused on a brand;   presenting the brand-centric websites to a remote computer based on the attributes;   receiving a selection of the one of the brand-centric websites from the remote computer;   analyzing the one of the brand-centric websites to search a computer network to generate suggestions of content-related websites in which an advertisement is to be placed, wherein the content-related websites in which the advertisement is to be placed has less information regarding the brand than that in the one of the brand-centric websites in which the advertisement is to be placed, wherein data for generating content of the one of the brand-centric websites and the content-related websites is obtained by a harvester, wherein a data type processor is configured to classify the data into video, audio, and text to generate classified data, wherein the classified data is stored in an entertainment content repository, wherein the content-related websites request the classified data via corresponding application programming interfaces from the content repository;   receiving a selection of one or more of the content-related websites from the remote computer;   obtaining metrics for similar advertisements when placed on a plurality of selected websites, the selected websites including the one of the brand-centric websites and the one or more of the content-related websites;   processing the metrics to define an advertising model, the advertising model having a score correlated to effectiveness of the advertisement; and   optimizing the advertising model to define a recommended advertising model, the recommended advertising model defining optimal suggestions of websites including the one of the brand-centric websites that has the classified data obtained from the entertainment content repository and in which the advertisement is to be placed.   
     
     
         20 . The computer-readable medium of  claim 19 , wherein the optimizing of the advertising model includes executing multivariable optimization to enable emphasis or non-emphasis of selection criteria.