Dynamic promotion analytics

Abstract

A promotion program analytical system and method is disclosed. The promotion program analytical system and method selects a promotion program to offer to a consumer. Selection of the promotion program to present to the consumer includes determining a probability that the consumer will accept the promotion program. The probability of acceptance may be determined based on past performance data of similar promotion programs, and also past performance data on the promotion program itself when it is available.

1 .- 24 . (canceled) 
     
     
         25 . A method for determining whether to provide a particular offer, from a promotion program, to a consumer device associated with a particular consumer, the method comprising:
 deriving, via a processor, from the promotion program, a first promotion program attribute and a duration, wherein the duration is comprised of a plurality of time periods;   generating, using a historical predictive model, a historical predicted probability, wherein the historical predicted probability is based on performance data from one or more different promotion programs and consumer attribute data associated with the particular consumer;   generating, using a promotion program predictive model, a promotion program predicted probability, wherein the promotion program predicted probability is based on real performance data from the promotion program and the consumer attribute data;   determining sufficient of real performance data based on whether an amount of the real performance data is greater than each of a first threshold and a second threshold;   determining a final predicted probability that the particular consumer will accept the particular offer based on the determination of whether the amount of real performance data is sufficient, wherein the final predicted probability is a function of the historical predicted probability, the promotion program predicted probability, or the historical predicted probability and the promotion program predicted probability;   dynamically and iteratively updating the promotion program predictive model as additional real performance data from the promotion program is available, wherein the additional real performance data includes performance data from a previous time period; and   as a result of the updating of the promotion program predictive model, re-determining sufficiency of the real performance data and re-determining the final predicted probability that the particular consumer will accept the particular offer, resulting in gradual migration from a reliance on the output of the historical predicted probability based on performance data from one or more different promotion programs to reliance on the output of the promotion program predicted probability based on performance data from the promotion program.   
     
     
         26 . The method of  claim 25 , further comprising:
 providing, for display on the consumer device, the particular offer via an electronic communication upon a determination that the final predicted probability that the particular consumer will accept the particular offer is within a predefined delta.   
     
     
         27 . The method of  claim 25  further comprising:
 determining that the final predicted probability that the particular consumer will accept the particular offer is not within the predefined delta; and 
 determining whether the real performance data indicates that a desired number of consumers in a selected grouping have been provided the particular offer, wherein the real performance data is indicative of a number of consumers with a first promotion program attribute value of the derived first promotion program attribute that received the particular offer from the promotion program, 
 wherein determining whether the real performance data is sufficient comprises comparing the number of consumers with the first promotion program attribute value that received the particular offer from the promotion program to a predetermined number. 
 
     
     
         28 . The method of  claim 27 , further comprising:
 determining whether there are any other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program; and   in an instance in which the determination is made that there are not other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program, increasing the delta.   
     
     
         29 . The method of  claim 27 , further comprising:
 determining whether there are any other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program;   in an instance in which the determination is made that there are not other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program;   determining a new final predicted probability that a new particular consumer will accept the particular offer; and   determining that the new final predicted probability that the new particular consumer will accept the particular offer is within the predefined delta; and   providing, for display on a consumer device associated with the new particular consumer, the particular offer via the electronic communication.   
     
     
         30 . The method of  claim 25 , wherein the real performance data includes a number of consumers that accepted the particular offer in a previous time period or a percentage of consumers that accepted the particular offer. 
     
     
         31 . The method of  claim 25 , further comprising:
 dynamically updating the promotion program predictive model at one or more discrete times during the duration of the promotion program.   
     
     
         32 . A computer program product for determining whether to provide a particular offer, from a promotion program, to a consumer device associated with a particular consumer, the computer program product, stored on a non-transitory computer readable medium, comprising instructions that when executed on one or more computers cause the one or more computers to perform operations the operations comprising:
 deriving, via a processor, from the promotion program, a first promotion program attribute and a duration, wherein the duration is comprised of a plurality of time periods;   generating, using a historical predictive model, a historical predicted probability, wherein the historical predicted probability is based on performance data from one or more different promotion programs and consumer attribute data associated with the particular consumer;   generating, using a promotion program predictive model, a promotion program predicted probability, wherein the promotion program predicted probability is based on real performance data from the promotion program and the consumer attribute data;   determining sufficient of real performance data based on whether an amount of the real performance data is greater than each of a first threshold and a second threshold;   determining a final predicted probability that the particular consumer will accept the particular offer based on the determination of whether the amount of real performance data is sufficient, wherein the final predicted probability is a function of the historical predicted probability, the promotion program predicted probability, or the historical predicted probability and the promotion program predicted probability;   dynamically and iteratively updating the promotion program predictive model as additional real performance data from the promotion program is available, wherein the additional real performance data includes performance data from a previous time period; and   as a result of the updating of the promotion program predictive model, re-determining sufficiency of the real performance data and re-determining the final predicted probability that the particular consumer will accept the particular offer, resulting in gradual migration from a reliance on the output of the historical predicted probability based on performance data from one or more different promotion programs to reliance on the output of the promotion program predicted probability based on performance data from the promotion program.   
     
     
         33 . The computer program product of  claim 32 , the operations further comprising:
 providing, for display on the consumer device, the particular offer via an electronic communication upon a determination that the final predicted probability that the particular consumer will accept the particular offer is within a predefined delta.   
     
     
         34 . The computer program product of  claim 32 , the operations further comprising:
 determining that the final predicted probability that the particular consumer will accept the particular offer is not within the predefined delta; and   determining whether the real performance data indicates that a desired number of consumers in a selected grouping have been provided the particular offer, wherein the real performance data is indicative of a number of consumers with a first promotion program attribute value of the derived first promotion program attribute that received the particular offer from the promotion program,   wherein determining whether the real performance data is sufficient comprises comparing the number of consumers with the first promotion program attribute value that received the particular offer from the promotion program to a predetermined number.   
     
     
         35 . The computer program product of  claim 34 , the operations further comprising:
 determining whether there are any other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program; and   in an instance in which the determination is made that there are not other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program, increasing the delta.   
     
     
         36 . The computer program product of  claim 34 , the operations further comprising:
 determining whether there are any other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program;   in an instance in which the determination is made that there are not other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program;   determining a new final predicted probability that a new particular consumer will accept the particular offer; and   determining that the new final predicted probability that the new particular consumer will accept the particular offer is within the predefined delta; and   providing, for display on a consumer device associated with the new particular consumer, the particular offer via the electronic communication.   
     
     
         37 . The computer program product of  claim 32 , wherein the real performance data includes a number of consumers that accepted the particular offer in a previous time period or a percentage of consumers that accepted the particular offer. 
     
     
         38 . The computer program product of  claim 32 , the operations further comprising:
 dynamically updating the promotion program predictive model at one or more discrete times during the duration of the promotion program.   
     
     
         39 . An apparatus for determining whether to provide a particular offer, from a promotion program, to a consumer device associated with a particular consumer, the apparatus comprising:
 one or more memories configured to store one or more consumer profiles, promotion program data of offers relating to the promotion program, and historical data of offers relating to different promotion programs; and   a processor in communication with the one or more memories, the processor configured to:   derive, via a processor, from the promotion program, a first promotion program attribute and a duration, wherein the duration is comprised of a plurality of time periods;   generate, using a historical predictive model, a historical predicted probability, wherein the historical predicted probability is based on performance data from one or more different promotion programs and consumer attribute data associated with the particular consumer;   generate, using a promotion program predictive model, a promotion program predicted probability, wherein the promotion program predicted probability is based on real performance data from the promotion program and the consumer attribute data;   determine sufficient of real performance data based on whether an amount of the real performance data is greater than each of a first threshold and a second threshold;   determine a final predicted probability that the particular consumer will accept the particular offer based on the determination of whether the amount of real performance data is sufficient, wherein the final predicted probability is a function of the historical predicted probability, the promotion program predicted probability, or the historical predicted probability and the promotion program predicted probability;   dynamically and iteratively update the promotion program predictive model as additional real performance data from the promotion program is available, wherein the additional real performance data includes performance data from a previous time period; and   as a result of the update of the promotion program predictive model, re-determine sufficiency of the real performance data and re-determine the final predicted probability that the particular consumer will accept the particular offer, resulting in gradual migration from a reliance on the output of the historical predicted probability based on performance data from one or more different promotion programs to reliance on the output of the promotion program predicted probability based on performance data from the promotion program.   
     
     
         40 . The apparatus of  claim 39 , wherein the processor is further configured to:
 provide, for display on the consumer device, the particular offer via an electronic communication upon a determination that the final predicted probability that the particular consumer will accept the particular offer is within a predefined delta.   
     
     
         41 . The apparatus of  claim 39 , wherein the processor is further configured to:
 determine that the final predicted probability that the particular consumer will accept the particular offer is not within the predefined delta; and   determine whether the real performance data indicates that a desired number of consumers in a selected grouping have been provided the particular offer, wherein the real performance data is indicative of a number of consumers with a first promotion program attribute value of the derived first promotion program attribute that received the particular offer from the promotion program,   wherein determining whether the real performance data is sufficient comprises comparing the number of consumers with the first promotion program attribute value that received the particular offer from the promotion program to a predetermined number.   
     
     
         42 . The apparatus of  claim 41 , wherein the processor is further configured to:
 determine whether there are any other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program; and   in an instance in which the determination is made that there are not other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program, increase the delta.   
     
     
         43 . The apparatus of  claim 41 , wherein the processor is further configured to:
 determine whether there are any other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program;   in an instance in which the determination is made that there are not other consumers to consider in the selected grouping that have not yet been provided the particular offer from the promotion program;   determine a new final predicted probability that a new particular consumer will accept the particular offer;   determine that the new final predicted probability that the new particular consumer will accept the particular offer is within the predefined delta; and   provide, for display on a consumer device associated with the new particular consumer, the particular offer via the electronic communication.   
     
     
         44 . The apparatus of  claim 39 , wherein the processor is further configured to:
 dynamically update the promotion program predictive model at one or more discrete times during the duration of the promotion program.