Advertisement generation and optimization

Abstract

Methods, apparatuses, and articles of manufacture for generating advertisements using an algorithmic system, such as a combinatoric system, and determining effectiveness metrics or predictions for the advertisements are described herein.

1 . A method comprising:
 receiving, by a computing device, at least one algorithmic expression implicitly expressing a plurality of advertisements; and   analyzing, by the computing device, the at least one algorithmic expression in view of one or more models of advertisement effectiveness to select an advertisement of the plurality of advertisements.   
     
     
         2 . The method of  claim 1 , wherein the at least one algorithmic expression is defined based on one or both of user inputs and/or computational-linguistic methods. 
     
     
         3 . The method of  claim 1 , further comprising generating the selected advertisement after selection of its content via the at least one algorithmic expression. 
     
     
         4 . The method of  claim 1 , wherein the plurality of advertisements are ad copy and the at least one algorithmic expression is a combinatoric expression comprising a base ad copy and a plurality of advertisement variables. 
     
     
         5 . The method of  claim 4 , wherein the plurality of advertisement variables include at least one of a term, a phrase, a noun, an adjective, a verb, an adverb, spacing, capitalization, or number and/or kind of punctuation marks. 
     
     
         6 . The method of  claim 4 , wherein said analyzing further comprises
 generating a number of ad copy having differing values for an advertisement variable of the combinatoric expression, and   comparing each ad copy to at least one other ad copy for which one or more effectiveness metrics are known.   
     
     
         7 . The method of  claim 1 , wherein the plurality of advertisements are candidate advertisements for placement within a media object, and the one or more models of advertisement effectiveness include user characteristics and/or usage patterns. 
     
     
         8 . The method of  claim 1 , wherein the one or more models of advertisement effectiveness are based on previous empirical evaluations of other advertisements, and the other advertisements are determined by machine learning methods. 
     
     
         9 . The method of  claim 1 , wherein the effectiveness metrics include click-through rate and/or conversions. 
     
     
         10 . A method comprising:
 receiving, by a computing device, an advertisement generated based on at least one algorithmic expression implicitly expressing a plurality of advertisements; and   deploying, by the computing device, the advertisement to determine one or more metrics of effectiveness to be associated with the advertisement based on user reactions to the advertisement.   
     
     
         11 . The method of  claim 10 , further comprising generating the plurality of advertisements, including the advertisement, based on a plurality of combinations of values of at least one advertisement variable of the at least one algorithmic expression. 
     
     
         12 . The method of  claim 10 , further comprising receiving the at least one algorithmic expression implicitly expressing the plurality of advertisements, the at least one algorithmic expression defined based on one or both of user inputs and/or computational-linguistic methods. 
     
     
         13 . The method of  claim 10 , wherein the plurality of advertisements are ad copy and the at least one algorithmic expression is a combinatoric expression comprising a base ad copy and a plurality of advertisement variables. 
     
     
         14 . The method of  claim 13 , wherein the plurality of advertisement variables include at least one of a term, a phrase, a noun, an adjective, a verb, an adverb, spacing, capitalization, or number and/or kind of punctuation marks. 
     
     
         15 . The method of  claim 10 , wherein the one or more metrics of effectiveness include at least one of click-through rates, conversions, revenue generated, mouse-over events, and passive gaze-tracking, and the user reactions include at least one of mouse-clicks, gazing, and transactions. 
     
     
         16 . The method of  claim 10 , wherein the advertisement is deployed online and is accessible through keyword searches on search engines. 
     
     
         17 . The method of  claim 10 , further comprising storing the one or more metrics of effectiveness in a database. 
     
     
         18 . An apparatus comprising:
 a processor; and   logic operated by the processor and adapted to:
 receive at least one algorithmic expression implicitly expressing a plurality of advertisements, defined based on one or both of user inputs and/or computational-linguistic methods, 
 generate an advertisement of the plurality of advertisements based on the at least one algorithmic expression for the plurality of advertisements, and 
 deploy the advertisement to determine one or more metrics of effectiveness to be associated with the advertisement based on user reactions to the advertisement. 
   
     
     
         19 . The apparatus of  claim 18 , wherein the plurality of advertisements are ad copy and the at least one algorithmic expression is a combinatoric expression comprising a base ad copy and a plurality of advertisement variables. 
     
     
         20 . The apparatus of  claim 17 , wherein the one or more metrics of effectiveness include at least one of click-through rates, conversions, revenue generated, mouse-over events, and passive gaze-tracking, and the user reactions include at least one of mouse-clicks, gazing, and transactions. 
     
     
         21 . An article of manufacture comprising:
 a storage medium; and   a plurality of programming instructions stored on the storage medium and configured to program a computing device to:
 receive at least one algorithmic expression for a plurality of candidate advertisements of a media object, and 
 analyze the at least one algorithmic expression in view of one or more user characteristics and/or usage patterns to select an advertisement of the plurality of candidate advertisements to present within the media object. 
   
     
     
         22 . The article of  claim 21 , wherein the media object has a plurality of locations for placement of ones of the plurality of candidate advertisements. 
     
     
         23 . The article of  claim 21 , wherein the plurality of programming instructions are further configured to program the computing device to send a bill to a broadcast server for the advertiser associated with the selected advertisement. 
     
     
         24 . The article of  claim 21 , wherein the plurality of programming instructions are further configured to program the computing device to determine two or more of the plurality of candidate advertisements based on said analysis, and to auction presentation within the media object to one of the advertisers associated with the two or more determined advertisements. 
     
     
         25 . The article of  claim 21 , wherein the user characteristics and usage patterns include one or more of viewer tastes, preferences, and habits.