Method and System for Presenting Targeted Advertisements

Abstract

A method and system for presenting targeted advertisements to a subscriber includes extracting probabilistic information about subscriber activities from one or more source and processing the probabilistic information about subscriber activities to generate a subscriber characterization vector.

1 . A method of managing an advertisement system, the method comprising:
 (a) accessing a plurality of consumer information records corresponding to a plurality of consumers, each consumer information record comprising consumer data in at least two information categories;   (b) accessing an advertisement and a corresponding ad characterization record, the advertisement characterization record comprising target characteristics for the at least two information categories;   (c) generating an index score for each information category in each consumer information record by correlating the consumer data in the at least two information categories of the consumer information records with the target characteristics for the at least two information categories in the ad characterization record;   (d) identifying, based on the index scores, at least one target consumer to receive the advertisement.   
     
     
         2 . The method of  claim 1 , further comprising:
 (e) calculating an estimated consumer interest value for each of the plurality of consumers by using a correlation coefficient.   
     
     
         3 . The method of  claim 2 , wherein the correlation coefficient is the Pearson product-moment coefficient. 
     
     
         4 . The method of  claim 1 , wherein the at least one target consumer is identified by:
 (i) summing the index scores in each information category for each consumer to determine a plurality of summed index scores;   (ii) retrieving a predetermined summed index score corresponding to the ad characterization record; and   (iii) selecting at least one consumer with a summed index score equal to or greater than the predetermined summed index score.   
     
     
         5 . The method of  claim 4 , wherein the summed index scores reflect a probability that the corresponding consumer is interested in the advertisement. 
     
     
         6 . The method of  claim 1 , wherein the index score for each information category is determined through the use of one or more previously developed heuristic rules, wherein the previously developed heuristic rules relate consumer information to the target characteristics in at least one of the information categories. 
     
     
         7 . The method of  claim 6 , wherein the previously developed heuristic rules are probabilistic in nature. 
     
     
         8 . A method of managing an advertisement system, the method comprising:
 (a) accessing a plurality of consumer information records corresponding to a plurality of consumers, wherein the plurality of consumer information records include demographic information and product preference information corresponding to the respective consumer;   (b) generating a plurality of consumer index scores based on the consumer information records, wherein each of the consumer index scores corresponds to the respective consumer;   (c) accessing an advertisement and a corresponding advertisement characterization profile, wherein the advertisement characterization profile comprises target characteristics of the corresponding advertisement;   (d) generating an advertisement index score based on the advertisement characterization profile; and   (e) calculating an estimated consumer interest value for each of the plurality of consumers by correlating the plurality of consumer index scores with the advertisement index score.   
     
     
         9 . The method of  claim 8 , further comprising:
 (f) identifying, based on the estimated consumer interest value, at least one target consumer to receive the advertisement.   
     
     
         10 . The method of  claim 8 , wherein the calculating the estimated consumer interest value uses a correlation coefficient. 
     
     
         11 . The method of  claim 10 , wherein the correlation coefficient is the Pearson product-moment coefficient. 
     
     
         12 . The method of  claim 8 , wherein the index scores reflect a probability that the corresponding consumer is interested in a predefined interest category. 
     
     
         13 . The method of  claim 12 , wherein the index score is generated based on one or more previously developed heuristic rules, wherein the previously developed heuristic rules relate consumer information to a target characteristic of the predefined interest category. 
     
     
         14 . The method of  claim 13 , wherein the previously developed heuristic rules are probabilistic in nature. 
     
     
         15 . A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, said computer readable program code adapted for execution on a computer to implement a method of managing an advertisement system, said method comprising:
 (a) accessing a plurality of consumer information records corresponding to a plurality of consumers, each consumer information record comprising consumer data in at least two information categories;   (b) accessing an advertisement and a corresponding ad characterization record, the advertisement characterization record comprising target characteristics for the at least two information categories;   (c) generating an index score for each information category in each consumer information record by correlating the consumer data in the at least two information categories of the consumer information records with the target characteristics for the at least two information categories in the ad characterization record;   (d) identifying, based on the index scores, at least one target consumer to receive the advertisement.   
     
     
         16 . The computer program product of  claim 15 , further comprising:
 (e) calculating an estimated consumer interest value for each of the plurality of consumers by using a correlation coefficient.   
     
     
         17 . The computer program product of  claim 16 , wherein the correlation coefficient is the Pearson product-moment coefficient. 
     
     
         18 . The computer program product of  claim 15 , wherein the at least one target consumer is identified by:
 (i) summing the index scores in each information category for each consumer to determine a plurality of summed index scores;   (ii) retrieving a predetermined summed index score corresponding to the ad characterization record; and   (iii) selecting at least one consumer with a summed index score equal to or greater than the predetermined summed index score.   
     
     
         19 . An advertisement matching system in a computing environment, said system comprising:
 an electronic storage unit configured to store a plurality of consumer information records, the records comprising consumer data in at least two information categories;   a receiving unit configured to receive advertisement data including an advertisement and a corresponding advertisement characterization record, the advertisement characterization record comprising target characteristics for the at least two information categories; and   a processor configured to:
 (i) interpret the consumer information records and the advertisement characterization record; 
 (ii) generate an index score for each information category in each consumer information record by correlating the consumer data in the at least two information categories of the consumer information records with the target characteristics for the at least two information categories in the advertisement characterization record; and 
 (iii) identify, based on the index scores, at least one target consumer to receive the advertisement. 
   
     
     
         20 . The advertisement matching system of  claim 19 , further comprising:
 an advertisement delivery unit for delivering the advertisement to the at least one target consumer.