System and method for targeting content based on filter activity

Abstract

Various embodiments are presented which comprise an electronic catalog of products, wherein the catalog comprises a taxonomy of product categories and products within the categories, wherein various users input filter parameters and these are monitored, whereupon a new set of filter parameters are accepted and compared to the past set of filter parameters to generate content recommendations.

1 . A computer system, comprising:
 a database module that stores an electronic catalog of products, wherein the catalog comprises a taxonomy of product categories and products within the categories, the catalog further comprising attributes which describe products in a category and at least one value for said attributes;   a user interface module configured to accept current filter parameters relating to at least one of the categories and values of the attributes in response to a selection by the user;   a query module configured to receive the current filter parameters, query the catalog, and present information in the catalog corresponding to the filter parameters to said user interface module for display to users;   a monitoring module that monitors the current filter parameters to generate a set of user activity data comprising plural previous filter parameters;   a user activity data analysis module, configured to compare said user activity data with the current filter parameters to generate one or more content recommendations.   
     
     
         2 . The system of  claim 1 , wherein said filter parameters include a set of parameters requiring one or more of, when applied in said query module: a given attribute equals a specific value; a given attribute is not equal to a specific value; a given attribute is greater than a specific value; a given attribute is greater than or equal to a specific value; a given attribute is less than a specific value; a given attribute is less than or equal to a specific value; a given attribute falls within a specific interval; a given attribute falls outside of a specific interval. 
     
     
         3 . The system of  claim 2 , wherein said recommendations are based on an identification of one or more values of one or more attributes which occurred most frequently when or more attributes are above and/or above or equal to and/or equal to and/or less than and/or less than or equal to a predefined or user-input threshold within the set of user activity data and/or one or more values of one or more attributes within a set range. 
     
     
         4 . The system of  claim 1 , wherein said user activity data analysis module accepts input from said user interface module to restrict the time interval over which said filter parameters are collected for use in the data analysis. 
     
     
         5 . The system of  claim 1 , wherein said recommendations are based on an identification of one or more values of one or more attributes which occurred most or least frequently when or more attributes are equal to a predefined or user-input value within the set of user activity data. 
     
     
         6 . The system of  claim 1 , wherein said attributes include brand. 
     
     
         7 . The system of  claim 6 , wherein said user activity data analysis module generates a content recommendation where, if brand is held constant as set to the brand of the user, of products with proportions greater than a set threshold of the total user activity data with respect to the total set of user activity data. 
     
     
         8 . The system of  claim 6 , wherein said user activity data analysis module generates a content recommendation where, if no individual value of brand has an incidence in the user activity data of greater than a predetermined or user-input threshold, then the user data analysis module recommends that type of product as one where a new brand may be a good target for advertising. 
     
     
         9 . The system of  claim 6 , further comprising a user identity data module, which assists said monitoring module to additionally associate user identity data with said user activity data. 
     
     
         10 . The system of  claim 9 , wherein said user activity data analysis module associates said user identity data with said incidences of brands and if an individual user's proportion of a specific brand in their choice of filters is greater than a predetermined or user-input threshold, then the user data analysis module recommends that type of product as one where a new brand may be a good target for advertising. 
     
     
         11 . The system of  claim 1 , further comprising an targeted advertising display module, which displays targeted advertisements based on said user activity data. 
     
     
         12 . The system of  claim 11 , wherein the targeted advertising display module displays said targeted advertisements along with the contents of said catalog in a web browser. 
     
     
         13 . The system of  claim 1 , wherein said products are digital media. 
     
     
         14 . The system of  claim 13 , wherein said digital media products consist of one or more of digital text, audio, MIDI data, recorded audiobooks, digital music, bitmapped and/or vector graphics, digital photographs, video, movies, TV episodes, digital documents, animations, software, web content, multimedia, or encoded or archived data. 
     
     
         15 . The system of  claim 14 , wherein the catalog contains items of digital content and items of merchandise, and some items of digital content are associated with the items of merchandise. 
     
     
         16 . The system of  claim 15 , wherein user activity data for said digital content is used to generate targeted advertisements for items of merchandise, or vice versa. 
     
     
         17 . A method involving steps to be performing on a computing system consisting of multiple modules designed to perform computing functions which transform data monitoring results, wherein at least part of the computing system's functionality is performed by hardware, comprising:
 storing an electronic catalog of products with a database module, wherein the catalog comprises a taxonomy of product categories and products within the categories, the catalog further comprising attributes which describe products in a category and at least one value for said attributes;   accepting with a user interface module configured to accept current filter parameters relating to at least one of the categories and values of the attributes in response to a selection by the user;   receiving with a query module configured to receive the current filter parameters, querying with said query module the catalog, and presenting with said query module information in the catalog corresponding to the filter parameters to said user interface module for display to users;   monitoring with a monitoring module that monitors the current filter parameters to generate a set of user activity data comprising plural previous filter parameters;   and comparing with a user activity data analysis module, that is configured to compare said user activity data with the current filter parameters to generate one or more content recommendations.   
     
     
         18 . The method of  claim 17 , wherein said filter parameters include a set of parameters requiring one or more of, when applied in said query module: a given attribute equals a specific value; a given attribute is not equal to a specific value; a given attribute is greater than a specific value; a given attribute is greater than or equal to a specific value; a given attribute is less than a specific value; a given attribute is less than or equal to a specific value; a given attribute falls within a specific interval; a given attribute falls outside of a specific interval. 
     
     
         19 . The method of  claim 18 , wherein said recommendations are based on an identification of one or more values of one or more attributes which occurred most frequently when or more attributes are above and/or above or equal to and/or equal to and/or less than and/or less than or equal to a predefined or user-input threshold within the set of user activity data and/or one or more values of one or more attributes within a set range. 
     
     
         20 . The method of  claim 17 , wherein said user activity data analysis module accepts input from said user interface module to restrict the time interval over which said filter parameters are collected for use in the data analysis. 
     
     
         21 . The method of  claim 17 , wherein said recommendations are based on an identification of one or more values of one or more attributes which occurred most or least frequently when or more attributes are equal to a predefined or user-input value within the set of user activity data. 
     
     
         22 . The method of  claim 17 , wherein said attributes include brand. 
     
     
         23 . The method of  claim 22 , wherein said user activity data analysis module generates a content recommendation where, if brand is held constant as set to the brand of the user, of products with high proportions of the total user activity data with respect to the total set of user activity data. 
     
     
         24 . The method of  claim 22 , wherein said user activity data analysis module generates a content recommendation where, if no individual value of brand has an incidence in the user activity data of greater than a predetermined or user-input threshold, then the user data analysis module recommends that type of product as one where a new brand may be a good target for advertising. 
     
     
         25 . The method of  claim 22 , further comprising a user identity data module, which assists said monitoring module to additionally associate user identity data with said user activity data. 
     
     
         26 . The method of  claim 25 , wherein said user activity data analysis module associates said user identity data with said incidences of brands and if an individual user's proportion of a specific brand in their choice of filters is greater than a predetermined or user-input threshold, then the user data analysis module recommends that type of product as one where a new brand may be a good target for advertising. 
     
     
         27 . The method of  claim 17 , further comprising an targeted advertising display module, which displays targeted advertisements based on said user activity data. 
     
     
         28 . The method of  claim 27 , wherein the targeted advertising display module displays said targeted advertisements along with the contents of said catalog in a web browser. 
     
     
         29 . The method of  claim 17 , wherein said products are digital media. 
     
     
         30 . The method of  claim 29 , wherein said digital media products consist of one or more of digital text, audio, MIDI data, recorded audiobooks, digital music, bitmapped and/or vector graphics, digital photographs, video, movies, TV episodes, digital documents, animations, software, web content, multimedia, or encoded or archived data. 
     
     
         31 . The method of  claim 30 , wherein the catalog contains items of digital content and items of merchandise, and some items of digital content are associated with the items of merchandise. 
     
     
         32 . The method of  claim 31 , wherein user activity data for said digital content is used to generate targeted advertisements for items of merchandise, or vice versa. 
     
     
         33 . An apparatus designed to perform computing functions which transform data monitoring results, wherein at least part of the apparatus's functionality is performed by hardware, comprising:
 means for storing an electronic catalog of products with a database module, wherein the catalog comprises a taxonomy of product categories and products within the categories, the catalog further comprising attributes which describe products in a category and at least one value for said attributes;   means for accepting with a user interface module configured to accept current filter parameters relating to at least one of the categories and values of the attributes in response to a selection by the user;   means for receiving with a query module configured to receive the current filter parameters, means for querying with said query module the catalog and means for presenting with said query module information in the catalog corresponding to the filter parameters to said user interface module for display to users;   means for monitoring with a monitoring module that monitors the current filter parameters to generate a set of user activity data comprising plural previous filter parameters;   and means for comparing with user activity data analysis module, that is configured to compare said user activity data with the current filter parameters to generate one or more content recommendations.   
     
     
         34 . The apparatus of  claim 33 , wherein said filter parameters include a set of parameters requiring one or more of, when applied in said query module: a given attribute equals a specific value; a given attribute is not equal to a specific value; a given attribute is greater than a specific value; a given attribute is greater than or equal to a specific value; a given attribute is less than a specific value; a given attribute is less than or equal to a specific value; a given attribute falls within a specific interval; a given attribute falls outside of a specific interval. 
     
     
         35 . The apparatus of  claim 34 , wherein said recommendations are based on an identification of one or more values of one or more attributes which occurred most frequently when or more attributes are above and/or above or equal to and/or equal to and/or less than and/or less than or equal to a predefined or user-input threshold within the set of user activity data and/or one or more values of one or more attributes within a set range. 
     
     
         36 . The apparatus of  claim 33 , wherein said user activity data analysis module accepts input from said user interface module to restrict the time interval over which said filter parameters are collected for use in the data analysis. 
     
     
         37 . The apparatus of  claim 33 , wherein said recommendations are based on an identification of one or more values of one or more attributes which occurred most or least frequently when or more attributes are equal to a predefined or user-input value within the set of user activity data. 
     
     
         38 . The apparatus of  claim 33 , wherein said attributes include brand. 
     
     
         39 . The apparatus of  claim 38 , wherein said user activity data analysis module generates a content recommendation where, if brand is held constant as set to the brand of the user, of products with high proportions of the total user activity data with respect to the total set of user activity data. 
     
     
         40 . The apparatus of  claim 38 , wherein said user activity data analysis module generates a content recommendation where, if no individual value of brand has an incidence in the user activity data of greater than a predetermined or user-input threshold, then the user data analysis module recommends that type of product as one where a new brand may be a good target for advertising. 
     
     
         41 . The apparatus of  claim 38 , further comprising a user identity data module, which assists said monitoring module to additionally associate user identity data with said user activity data. 
     
     
         42 . The apparatus of  claim 41 , wherein said user activity data analysis module associates said user identity data with said incidences of brands and if an individual user's proportion of a specific brand in their choice of filters is greater than a predetermined or user-input threshold, then the user data analysis module recommends that type of product as one where a new brand may be a good target for advertising. 
     
     
         43 . The apparatus of  claim 33 , further comprising an targeted advertising display module, which displays targeted advertisements based on said user activity data. 
     
     
         44 . The apparatus of  claim 43 , wherein the targeted advertising display module displays said targeted advertisements along with the contents of said catalog in a web browser. 
     
     
         45 . The apparatus of  claim 33 , wherein said products are digital media. 
     
     
         46 . The apparatus of  claim 45 , wherein said digital media products consist of one or more of digital text, audio, MIDI data, recorded audiobooks, digital music, bitmapped and/or vector graphics, digital photographs, video, movies, TV episodes, digital documents, animations, software, web content, multimedia, or encoded or archived data. 
     
     
         47 . The apparatus of  claim 46 , wherein the catalog contains items of digital content and items of merchandise, and some items of digital content are associated with the items of merchandise. 
     
     
         48 . The apparatus of  claim 47 , wherein user activity data for said digital content is used to generate targeted advertisements for items of merchandise, or vice versa. 
     
     
         49 . Computer readable media, having instructions stored thereon, wherein the instructions, when executed by a processor, perform computing functions which transform data monitoring results, comprising:
 instructions for storing an electronic catalog of products with a database module, wherein the catalog comprises a taxonomy of product categories and products within the categories, the catalog further comprising attributes which describe products in a category and at least one value for said attributes;   instructions for accepting with a user interface module configured to accept current filter parameters relating to at least one of the categories and values of the attributes in response to a selection by the user, instructions for receiving with a query module configured to receive the current filter parameters;   instructions for querying with said query module the catalog, and means for presenting with said query module information in the catalog corresponding to the filter parameters to said user interface module for display to users;   instructions for monitoring with a monitoring module that monitors the current filter parameters to generate a set of user activity data comprising plural previous filter parameters;   and instructions for comparing with user activity data analysis module, that is configured to compare said user activity data with the current filter parameters to generate one or more content recommendations.   
     
     
         50 . The computer readable media of  claim 49 , wherein said filter parameters include a set of parameters requiring one or more of, when applied in said query module: a given attribute equals a specific value; a given attribute is not equal to a specific value; a given attribute is greater than a specific value; a given attribute is greater than or equal to a specific value; a given attribute is less than a specific value; a given attribute is less than or equal to a specific value; a given attribute falls within a specific interval; a given attribute falls outside of a specific interval. 
     
     
         51 . The computer readable media of  claim 50 , wherein said recommendations are based on an identification of one or more values of one or more attributes which occurred most frequently when or more attributes are above and/or above or equal to and/or equal to and/or less than and/or less than or equal to a predefined or user-input threshold within the set of user activity data and/or one or more values of one or more attributes within a set range. 
     
     
         52 . The computer readable media of  claim 49 , wherein said user activity data analysis module accepts input from said user interface module to restrict the time interval over which said filter parameters are collected for use in the data analysis. 
     
     
         53 . The computer readable media of  claim 49 , wherein said recommendations are based on an identification of one or more values of one or more attributes which occurred most or least frequently when or more attributes are equal to a predefined or user-input value within the set of user activity data. 
     
     
         54 . The computer readable media of  claim 49 , wherein said attributes include brand. 
     
     
         55 . The computer readable media of  claim 54 , wherein said user activity data analysis module generates a content recommendation where, if brand is held constant as set to the brand of the user, of products with high proportions of the total user activity data with respect to the total set of user activity data. 
     
     
         56 . The computer readable media of  claim 54 , wherein said user activity data analysis module generates a content recommendation where, if no individual value of brand has an incidence in the user activity data of greater than a predetermined or user-input threshold, then the user data analysis module recommends that type of product as one where a new brand may be a good target for advertising. 
     
     
         57 . The computer readable media of  claim 54 , further comprising a user identity data module, which assists said monitoring module to additionally associate user identity data with said user activity data. 
     
     
         58 . The computer readable media of  claim 57 , wherein said user activity data analysis module associates said user identity data with said incidences of brands and if an individual user's proportion of a specific brand in their choice of filters is greater than a predetermined or user-input threshold, then the user data analysis module recommends that type of product as one where a new brand may be a good target for advertising. 
     
     
         59 . The computer readable media of  claim 49 , further comprising an targeted advertising display module, which displays targeted advertisements based on said user activity data. 
     
     
         60 . The computer readable media of  claim 59 , wherein the targeted advertising display module displays said targeted advertisements along with the contents of said catalog in a web browser. 
     
     
         61 . The computer readable media of  claim 49 , wherein said products are digital media. 
     
     
         62 . The computer readable media of  claim 61 , wherein said digital media products consist of one or more of digital text, audio, MIDI data, recorded audiobooks, digital music, bitmapped and/or vector graphics, digital photographs, video, movies, TV episodes, digital documents, animations, software, web content, multimedia, or encoded or archived data. 
     
     
         63 . The computer readable media of  claim 62 , wherein the catalog contains items of digital content and items of merchandise, and some items of digital content are associated with the items of merchandise. 
     
     
         64 . The computer readable media of  claim 63 , wherein user activity data for said digital content is used to generate targeted advertisements for items of merchandise, or vice versa.