Systems and methods for distributing advertisements for selected content based on brand, content, and audience personality

Abstract

The invention includes systems and methods for selecting and distributing content based on personality. The invention provides an insight generation tool that receives brand, audience, and content personalities and profile elements and determines and provides client and agency insights. Brand personality is matched with audience personality is matched with content personality. Profile elements of the brand, the audience, and the content are matched. Agency content and branded media content is identified, selected, and distributed, and is distributed over video distribution networks based on the relationship between the brand personality, the media content personality, and the audience personality. The invention improves the effectiveness of targeted advertising of media content providers by evaluating multiplatform content offerings and identifies content that has the closest personality. Advertising customers can then take advantage of this match and associate their advertisements to that content, thus providing audiences with a more effective, context-based communication.

1 . A computer-implemented method for visualization and matching a brand with a media asset, the method comprising:
 receiving, in an insight generation server, a brand personality description from a cognitive computer server, the brand personality description determined based on recognized text representations of written brand communication materials created by a brand source;   analyzing, with the insight generation server, the brand personality description from the cognitive computer server based on the representations of the brand communications of the brand source, wherein the analyzing includes:
 identifying brand profile elements based on the brand personality description received from the cognitive computer server; 
 determining a central tendency and distribution for the brand profile elements; 
 constructing a brand profile element selection criteria based on the determined central tendency and distribution; and 
 filtering the brand profile elements for visualization based on the constructed brand profile element selection criteria; 
   generating a brand personality based on the brand personality analysis, wherein the brand personality includes the filtered profile elements of the brand;   receiving, in the insight generation server, a description of the media asset from the cognitive computer server, wherein the media asset description is based on recognized text representations of the media asset or a promotion for the media asset or a combination of both;   analyzing, with the insight generation server, the media asset description from the cognitive computer server, which produces a media asset personality description, wherein the analyzing includes:
 identifying media asset profile elements based on the media asset personality description received from the cognitive computer server; 
 determining a central tendency and distribution for the media asset profile elements; 
 constructing a media asset profile element selection criteria based on the determined central tendency and distribution; and 
 filtering the media asset profile elements for visualization based on the constructed media asset profile element selection criteria; 
   generating a media asset personality of the media asset based on the media asset personality analysis, wherein the media asset personality includes the filtered profile elements of the media asset;   reconciling the generated brand personality and the generated media asset personality, wherein the reconciliation includes:
 comparing the profile elements of the brand to the-profile elements of the media asset; 
 determining profile element vector distances between the brand profile elements and the media asset profile elements; and 
 matching the brand profile elements with the media asset profile elements based on the determined profile element vector distances; and 
   generating and presenting, by the insight generation server, a visualization of the reconciliation of the filtered brand profile elements and the filtered media asset profile elements to show a set of the matched filtered brand profile elements and the matched filtered media asset profile elements that represents a personality strength or a personality weaknesses of the brand and the media asset.   
     
     
         2 . A computer-implemented method of  claim 1 , further comprising:
 identifying the media asset in which to advertise the brand based on the generated visualization.   
     
     
         3 . A computer-implemented method of  claim 1 , further comprising:
 creating a branded content solution in which to advertise the brand, wherein the branded content solution includes a brand positioning based on a personality strength of the brand or a personality weakness of the brand based on the generated profile elements visualization, and wherein the brand positioning includes creating brand associations in customers' minds to influence the manner in which the customers perceive the brand.   
     
     
         4 . A computer-implemented method of  claim 3 , wherein the generated visualization includes a personality weakness of the brand, and the method further includes:
 comparing the brand to the market in which the brand operates by:
 ranking the brand profile elements based on profile element scores; 
 comparing the ranked profile elements to a predetermined profile element threshold, including an average score of the same profile elements of other brands; and 
 determining a brand weakness for those profile elements below the predetermined threshold; and 
   identifying a media asset in which to advertise the brand based on the generated visualization of the personality weakness of the brand.   
     
     
         5 . A computer-implemented method of  claim 3 , wherein the generated visualization includes a personality strength of the brand, and the method further includes:
 comparing the brand to the market in which the brand operates by:
 ranking the brand profile elements based on profile element scores; 
 comparing the ranked profile elements to a predetermined profile element threshold, including an average score of the same profile elements of other brands; and 
 determining a brand strength for those profile elements above the predetermined threshold; and 
   identifying a media asset in which to advertise the brand based on the generated visualization of the personality strength of the brand.   
     
     
         6 . A computer-implemented method of  claim 1 , further comprising:
 receiving, in the insight generation server, an audience personality description from the cognitive computer server, the audience personality description determined based on text representations and communications of audience characterizations;   analyzing, with the insight generation server, the audience personality description from the cognitive computer server based on the representations of the audience communications, wherein the analyzing includes:
 identifying audience profile elements based on the audience personality description received from the cognitive computer server; 
 determining a central tendency and distribution for the audience profile elements; 
 constructing an audience profile element selection criteria based on the determined central tendency and distribution; and 
 filtering the audience profile elements for visualization based on the constructed audience profile element selection criteria; 
   generating an audience personality based on the audience personality analysis, wherein the audience personality includes the filtered profile elements of the audience;   reconciling the generated audience personality and the generated brand personality, wherein the reconciliation includes
 comparing the audience profile elements to the brand profile elements; 
   determining profile element vector distances between the audience profile elements and the brand profile elements; and
 matching the-audience profile elements with the brand profile elements based on the determined profile element vector distances; and 
   generating and presenting, by the insight generation server, a visualization of the reconciliation of the matched filtered brand profile elements, the matched filtered media asset profile elements, and the matched filtered audience profile elements that represents a personality strength or a personality weakness of the audience, the brand, and the media asset.   
     
     
         7 . A computer-implemented method of  claim 6 , further comprising:
 receiving, in the insight generation server, a second audience personality description from the cognitive computer server, the second audience personality description determined based on text representations and communications of characterizations of a second audience;   analyzing, with the insight generation server, the second audience personality description from the cognitive computer server based on the representations of the second audience, wherein the analyzing includes:
 identifying second audience profile elements based on the second audience personality description received from the cognitive computer server; 
 determining a central tendency and distribution for the second audience profile elements; 
 constructing a second audience profile element selection criteria based on the determined central tendency and distribution; and 
 filtering the second audience profile elements for visualization based on the constructed second audience profile element selection criteria; 
   generating a second audience personality based on the second audience personality analysis, wherein the second audience personality includes the filtered profile elements of the second audience;   reconciling the generated second audience personality and the generated brand personality and the generated media asset personality, wherein the reconciliation includes:
 comparing the second audience profile elements to the brand profile elements; 
 determining profile element vector distances between the second audience profile elements and the-brand profile elements; and 
 matching the second audience profile elements with the brand profile elements based on the determined profile element vector distances; and 
   generating and presenting, by the insight generation server, a visualization of the reconciliation of the matched filtered brand profile elements, the matched filtered media asset profile elements, and the matched filtered second audience profile elements that represents a personality strength or a personality weakness of the second audience, the brand, and the media asset.   
     
     
         8 . A computer-implemented method of  claim 1 , further comprising:
 receiving, in the insight generation server, an additional brand personality description from the cognitive computer server, the additional brand personality description determined based on recognized text representations of written brand communication materials created by an additional brand source;   analyzing, with the insight generation server, the additional brand personality description from the cognitive computer server based on the representations of the additional brand, wherein the analyzing includes:
 identifying additional brand profile elements based on the additional brand personality description received from the cognitive computer server; 
 determining a central tendency and distribution for the additional brand profile elements; 
 constructing an additional brand profile element selection criteria based on the determined central tendency and distribution; and 
 filtering the additional brand profile elements for visualization based on the constructed additional brand profile element selection criteria; 
   generating an additional brand personality based on the additional brand personality analysis, wherein the additional brand personality includes the filtered profile elements of the additional brand;   reconciling the additional brand personality and the generated brand personality and the generated media asset personality, wherein the reconciliation includes:
 comparing the additional brand profile elements to the brand profile elements and to the media asset profile elements; 
 determining profile element vector distances between the-additional brand profile elements and the media asset profile elements and to the brand profile elements; and 
 matching the additional brand profile elements to the media asset profile elements and to the brand profile elements based on the determined profile element vector distances; and 
   generating and presenting a visualization of the reconciliation of the matched filtered brand profile elements and the matched filtered media asset profile elements and the matched filtered additional brand profile elements that represents a personality strength or a personality weakness of the additional brand, the brand, and the media asset.   
     
     
         9 . A computer-implemented method of  claim 8 , wherein the visualization includes at least twelve profile elements of the brand personality, the media asset personality, and the additional brand personality. 
     
     
         10 . A computer-implemented method of  claim 1 , wherein the comparison and matching of the media asset personality to the brand personality is based on at least ten profile elements of the brand personality and at least ten profile elements of the media asset personality. 
     
     
         11 . A computer-implemented method of  claim 1 , wherein the comparison of the media asset personality with the brand personality is based on the profile elements and the generated and presented visualization of the reconciliation of the brand profile elements and the media asset profile elements includes comparing at least ten most predominant profile elements of each of the media asset and of the brand and at least ten least predominant profile elements of each of the media asset and of the brand. 
     
     
         12 . A computer-implemented method of  claim 8 , wherein generating and presenting the visualization includes:
 generating a radar graph plotting profile elements of the brand, the media asset, and the additional brand; and   determining profile element vector distances between each of the plotted profile elements of the brand and the same profile elements of the media content, and wherein the matching is based on a multivariate profile element vector distance.   
     
     
         13 . A computer-implemented method of  claim 12 , further comprising:
 comparing at least ten most predominant brand personality traits to at least ten most predominant additional brand personality traits and to at least ten most predominant media asset personality traits;   comparing at least ten least predominant brand personality traits to at least ten least predominant additional brand personality traits and to at least ten least predominant media asset personality traits;   identifying an alternative media asset with alternative media asset personality traits that are more similar than the media asset personality traits of the media asset; and   substituting the alternative media asset for the media asset in an advertising campaign.   
     
     
         14 . A computer-implemented method of  claim 12 , further comprising:
 comparing at least ten most predominant brand personality traits to at least ten most predominant additional brand personality traits and to at least ten most predominant media asset personality traits;   comparing at least ten least predominant brand personality traits to at least ten least predominant additional brand personality traits and to at least ten least predominant media asset personality traits;   identifying an alternative media asset with alternative media asset personality traits that are more dissimilar than the media asset personality traits of the media asset; and   substituting the alternative media asset for the media asset in an advertising campaign.   
     
     
         15 . A system for visualization and matching a brand with a, media asset, the system comprising:
 an insight generation server, including a personality analysis application and a visualization and matching application stored on a non-transitory computer readable medium executed on a processor that   receives a brand personality description from a cognitive computer server, the brand personality description determined based on recognized text representations of written brand communication materials created by a brand source;   analyzes, with the personality analysis application on the insight generation server, the brand personality description from the cognitive computer server based on the representations of the brand communications of the brand source, wherein the analyzing includes:
 identifying a set of brand profile elements based on the brand personality description received from the cognitive computer server; 
 determining a central tendency and distribution for the brand profile elements; 
 constructing a brand profile element selection criteria based on the determined central tendency and distribution; and 
 filtering the brand profile elements for visualization based on the constructed brand profile element selection criteria; 
   generates a brand personality based on the brand personality analysis, wherein the brand personality includes the filtered profile elements of the brand;   receives, in the insight generation server, a description of the media asset from the cognitive computer server, wherein the media asset description is based on recognized text representations of the media asset or a promotion for the media asset or a combination of both;   analyzes, with the insight generation server, the media asset description from the cognitive computer server, which produces a media asset personality description, wherein the analyzing includes:
 identifying media asset profile elements based on the media asset personality description received from the cognitive computer server; 
 determining a central tendency and distribution for the media asset profile elements; 
 constructing a media asset profile element selection criteria based on the determined central tendency and distribution; and 
 filtering the media asset profile elements for visualization based on the constructed media asset profile element selection criteria; 
   generates a media asset personality based on the media asset analysis, wherein the media asset personality includes the filtered profile elements of the media asset;   reconciles the generated brand personality and the generated media asset personality, wherein the reconciliation includes:
 comparing the profile elements of the brand to the profile elements of the media asset; 
 determining profile element vector distances between the brand profile elements and the media asset profile elements; 
 matching the brand profile elements with the media asset profile elements based on the determined profile element vector distances; and 
 reducing the brand profile elements and media asset profile elements to be visualized to a predetermined number based on the matched filtered brand personality profile elements and the matched filtered media asset profile elements; 
   generates and presents, by the insight generation server, a visual representation of the reconciliation of the brand profile elements and the media asset profile elements to show a set of the matched filtered brand profile elements and the matched filtered media asset profile elements that represents a personality strength or a personality weaknesses of the brand and the media asset;   creates, by the insight generation server, a visual representation of the reconciliation of the brand profile elements and the media asset profile elements to show a set of the matched filtered brand profile elements and the matched filtered media asset profile elements that represents a personality strength or a personality weaknesses of the brand and the media asset; and   sends the visual representation for display on a graphical user interface.   
     
     
         16 . A system of  claim 15 , wherein the insight generation server receives brand profile element scores corresponding to the brand profile elements and receives content item profile element scores corresponding to the content item profile elements. 
     
     
         17 . A system of  claim 16 , wherein at least one of the group of the brand profile element scores and the content item element scores are received from a cognitive computer server. 
     
     
         18 . A system of  claim 16 , wherein the filtering and reduction of the set of brand profile elements to be visualized to a predetermined number based on the matched filtered brand profile elements and the matched filtered media asset profile elements includes:
 determining an aggregate profile element vector distance from each of the profile element scores of the brand profile elements to each of the respective media asset profile element scores; and   selecting a predetermined number of brand profile elements based upon the determined aggregate distance.   
     
     
         19 . A system of  claim 15 , wherein the insight generation server receives a set of audience profile elements and generates an audience personality based on the audience profile elements; and the reconciling includes reconciling the generated audience profile elements and the generated brand profile elements and the generated media asset profile elements. 
     
     
         20 . A system of  claim 19 , wherein the insight generation server creates a visual representation of the reduced set of brand profile elements including a graphical brand representation and a graphical media asset representation and a graphical audience representation and sends the visual representation for display on a graphical user interface.