Assumed demographics, predicted behavior, and targeted incentives

Abstract

A system and method for anticipating consumer behavior and determining transaction incentives for influencing consumer behavior comprises a computer system and associated database for determining cross time correlations between transaction behavior, for applying the function derived from the correlations to consumer records to predict future consumer behavior, and for deciding on transaction incentives to offer the consumers based upon their predicted behavior.

What is claimed is: 
     
         1 . A computer implemented method of predicting demographic traits of consumers based on purchase histories and identifying the predicted demographic traits that are most likely to be accurate, the method being implemented by a computer system having one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, cause the computer system to perform the method, the method comprising:
 obtaining, by the computer system, a first set of consumer records related to a plurality of first consumers, wherein each of the first set of consumer records includes: a first set of known demographic traits for a corresponding first consumer, and first purchase information that indicates one or more first purchases made by the corresponding first consumer;   obtaining, by the computer system, second purchase information that indicates one or more second purchases made by a second consumer;   comparing, by the computer system, the first purchase information and the second purchase information to determine one or more correlations between the first purchase information and the second purchase information;   determining, by the computer system, a set of assumed demographic traits of the second consumer based on the comparison and the first set of known demographic traits, wherein each assumed demographic trait: (i) predicts a demographic trait of the second consumer, and (ii) is associated with a probability that the assumed demographic trait is accurate;   selecting, by the computer system, a subset of the set of assumed demographic traits based on the their respective probabilities such that at least a first assumed demographic trait is selected over at least a second assumed demographic trait based on a first probability that the first assumed demographic trait is accurate and a second probability that the second assumed demographic trait is accurate; and   identifying, by the computer system, an incentive to provide to the second consumer based on the subset.   
     
     
         2 . The method of  claim 1 , the method further comprising:
 providing the incentive to the second consumer through at least a first communication channel from among a plurality of communication channels.   
     
     
         3 . The method of  claim 2 , the method further comprising:
 determining a redemption probability that indicates a likelihood of a redemption of the incentive by the second consumer if the incentive is provided through the first communication channel; and   determining whether to provide the incentive through the first communication channel based on the redemption probability.   
     
     
         4 . The method of  claim 1 , wherein the first assumed demographic trait relates to a first value for a given type of assumed demographic trait and the second assumed demographic trait relates to a second value for the given type of assumed demographic trait. 
     
     
         5 . The method of  claim 1 , wherein the first assumed demographic trait relates to a first type of assumed demographic trait and the second assumed demographic trait relates to a second type of assumed demographic trait. 
     
     
         6 . The method of  claim 1 , wherein selecting the subset comprises:
 filtering the set of assumed demographic traits based on: (i) respective values of each of the set of assumed demographic traits, (ii) respective types of each of the set of assumed demographic traits, and (iii) the respective probabilities that each of the set of assumed demographic traits is accurate.   
     
     
         7 . The method of  claim 6 , wherein filtering the set of assumed demographic traits comprises:
 filtering at least a first type of assumed demographic trait based on a first probability threshold and filtering at least a second type of assumed demographic trait based on a second probability threshold different from the first probability threshold.   
     
     
         8 . The method of  claim 1 , wherein a given probability that a given assumed demographic trait is accurate is based on a level of correlation between the first purchase information and the second purchase information. 
     
     
         9 . The method of  claim 1 , wherein a given probability that a given assumed demographic trait is accurate is based on a level of reliability of correlations between the first purchase information and the second purchase information in predicting the given assumed demographic trait. 
     
     
         10 . The method of  claim 1 , wherein selecting the subset comprises:
 ranking the set of assumed demographic traits with respect to each other based on the respective probabilities, such that the first demographic trait is ranked with respect to the second demographic trait, wherein the selected subset is based on the ranking.   
     
     
         11 . The method of  claim 1 , wherein the second consumer is associated with an assumed or known demographic trait that indicates a consumer location related to the second consumer, the method further comprising:
 determining a retail location associated with a retailer; and   correlating the consumer location with the retail location to determine whether the consumer location is within a certain region of the retail location, wherein the incentive is identified based further on the correlation.   
     
     
         12 . The method of  claim 11 , the method further comprising:
 determining a retail location associated with a retailer; and   performing demographic analysis based on the retail location and at least some of the set of assumed demographic traits.   
     
     
         13 . The method of  claim 12 , wherein the second consumer comprises a plurality of second consumers, and wherein the subset of the set of assumed demographic traits relates to a respective consumer location for each of the plurality of second consumers, wherein performing demographic analysis comprises:
 associating a set of the plurality of second consumers that made a purchase at the retailer with one or more regions within a certain proximity to the retail location based on the second purchase information and the respective consumer location for each of the plurality of second consumers; and   determining a number of consumers of the retailer in the one or more regions based on the association between the set of the plurality of second consumers and the one or more regions.   
     
     
         14 . The method of  claim 13 , the method further comprising:
 determining a total number of consumers that made a purchase at the retailer based on the second purchase information; and   calculating a fraction of consumers in the one or more regions relative to the total number of consumers based on the number and the total number; and   determining whether to provide the incentive based on the fraction.   
     
     
         15 . The method of  claim 12 , wherein the second consumer comprises a plurality of second consumers, and wherein the subset of the set of assumed demographic traits relate to a respective consumer location for each of the plurality of second consumers, wherein performing demographic analysis comprises:
 associating a set of the plurality of second consumers that made a purchase at the retailer with one or more regions within a certain proximity to the retail location based on the second purchase information and the respective consumer location for each of the plurality of second consumers; and   determining a value of purchases that the set of the plurality of second consumers in the one or more regions made at the retail location based on the association between the set of the plurality of second consumers and the one or more regions.   
     
     
         16 . The method of  claim 15 , the method further comprising:
 determining a total value of purchases made at the retailer based on the second purchase information; and   calculating a fraction of the value of purchases made in the one or more regions relative to the total value based on the value and the total value; and   determining whether to provide the incentive based on the fraction.   
     
     
         17 . A system of predicting demographic traits of consumers based on purchase histories and identifying the predicted demographic traits that are most likely to be accurate, the system comprising:
 a computer system comprising one or more physical processors programmed with computer program instructions to:   obtain a first set of consumer records related to a plurality of first consumers, wherein each of the first set of consumer records includes: a first set of known demographic traits for a corresponding first consumer, and first purchase information that indicates one or more first purchases made by the corresponding first consumer;   obtain second purchase information that indicates one or more second purchases made by a second consumer;   compare the first purchase information and the second purchase information to determine one or more correlations between the first purchase information and the second purchase information;   determine a set of assumed demographic traits of the second consumer based on the comparison and the first set of known demographic traits, wherein each assumed demographic trait: (i) predicts a demographic trait of the second consumer, and (ii) is associated with a probability that the assumed demographic trait is accurate;   select a subset of the set of assumed demographic traits based on the their respective probabilities such that at least a first assumed demographic trait is selected over at least a second assumed demographic trait based on a first probability that the first assumed demographic trait is accurate and a second probability that the second assumed demographic trait is accurate; and   identify an incentive to provide to the second consumer based on the subset.   
     
     
         18 . The system of  claim 17 , wherein the computer system is further programmed to:
 provide the incentive to the second consumer through at least a first communication channel from among a plurality of communication channels.   
     
     
         19 . The system of  claim 18 , wherein the computer system is further programmed to:
 determine a redemption probability that indicates a likelihood of a redemption of the incentive by the second consumer if the incentive is provided through the first communication channel; and   determine whether to provide the incentive through the first communication channel based on the redemption probability.   
     
     
         20 . The system of  claim 17 , wherein the first assumed demographic trait relates to a first value for a given type of assumed demographic trait and the second assumed demographic trait relates to a second value for the given type of assumed demographic trait. 
     
     
         21 . The system of  claim 17 , wherein the first assumed demographic trait relates to a first type of assumed demographic trait and the second assumed demographic trait relates to a second type of assumed demographic trait. 
     
     
         22 . The system of  claim 1 , wherein the computer system is further programmed to:
 filter the set of assumed demographic traits based on: (i) respective values of each of the set of assumed demographic traits, (ii) respective types of each of the set of assumed demographic traits, and (iii) the respective probabilities that each of the set of assumed demographic traits is accurate, wherein the subset is selected based on the filtered set of assumed demographic traits.   
     
     
         23 . The system of  claim 22 , wherein the computer system is further programmed to:
 filter at least a first type of assumed demographic trait based on a first probability threshold and filtering at least a second type of assumed demographic trait based on a second probability threshold different from the first probability threshold.   
     
     
         24 . The system of  claim 17 , wherein a given probability that a given assumed demographic trait is accurate is based on a level of correlation between the first purchase information and the second purchase information. 
     
     
         25 . The system of  claim 17 , wherein a given probability that a given assumed demographic trait is accurate is based on a level of reliability of correlations between the first purchase information and the second purchase information in predicting the given assumed demographic trait. 
     
     
         26 . The system of  claim 17 , wherein the computer system is further programmed to:
 rank the set of assumed demographic traits with respect to each other based on the respective probabilities, such that the first demographic trait is ranked with respect to the second demographic trait, wherein the selected subset is based on the rank.   
     
     
         27 . The system of  claim 17 , wherein the second consumer is associated with an assumed or known demographic trait that indicates a consumer location related to the second consumer, wherein the computer system is further programmed to:
 determine a retail location associated with a retailer; and   correlate the consumer location with the retail location to determine whether the consumer location is within a certain region of the retail location, wherein the incentive is identified based further on the correlation.   
     
     
         28 . The system of  claim 27 , wherein the computer system is further programmed to:
 determine a retail location associated with a retailer; and   perform demographic analysis based on the retail location and at least some of the set of assumed demographic traits.   
     
     
         29 . The system of  claim 28 , wherein the second consumer comprises a plurality of second consumers, and wherein the subset of the set of assumed demographic traits relates to a respective consumer location for each of the plurality of second consumers, wherein the computer system is further programmed to:
 associate a set of the plurality of second consumers that made a purchase at the retailer with one or more regions within a certain proximity to the retail location based on the second purchase information and the respective consumer location for each of the plurality of second consumers; and   determine a number of consumers of the retailer in the one or more regions based on the association between the set of the plurality of second consumers and the one or more regions.   
     
     
         30 . The system of  claim 29 , wherein the computer system is further programmed to:
 determine a total number of consumers that made a purchase at the retailer based on the second purchase information; and   calculate a fraction of consumers in the one or more regions relative to the total number of consumers based on the number and the total number; and   determine whether to provide the incentive based on the fraction.   
     
     
         31 . The system of  claim 28 , wherein the second consumer comprises a plurality of second consumers, and wherein the subset of the set of assumed demographic traits relate to a respective consumer location for each of the plurality of second consumers, wherein the computer system is further programmed to:
 associate a set of the plurality of second consumers that made a purchase at the retailer with one or more regions within a certain proximity to the retail location based on the second purchase information and the respective consumer location for each of the plurality of second consumers; and   determine a value of purchases that the set of the plurality of second consumers in the one or more regions made at the retail location based on the association between the set of the plurality of second consumers and the one or more regions.   
     
     
         32 . The system of  claim 31 , wherein the computer system is further programmed to:
 determine a total value of purchases made at the retailer based on the second purchase information; and   calculate a fraction of the value of purchases made in the one or more regions relative to the total value based on the value and the total value; and   determine whether to provide the incentive based on the fraction.