Adjustment of advertising schedule using performance trend

Abstract

Upper and lower boundary values can be determined based on estimated gross rating point (GRP) values associated with performance of an advertising schedule in a particular market. Audience data associated with the particular market, and a de-duplication weighting can be applied to the audience data to generate weighted audience data. Based at least in part on the weighted audience data, actual GRP values can be determined, and associated with the performance of the advertising schedule in the particular market. A predicted GRP trend can be determined based on those actual GRP values. The advertising schedule can be continually adjusted, in some cases in real time, to maintain the predicted GRP trend between the upper and lower boundary values.

What is claimed is: 
     
         1 . A method for use in a device configured to implement an automated media content scheduling system, the device including a memory and a processor programmed to implement the method, the method comprising:
 determining upper and lower boundary values based on estimated gross rating point (GRP) values associated with performance of an advertising schedule in a particular market;   obtaining audience data associated with the particular market;   applying a de-duplication weighting to audience data to generate weighted audience data;   determining, based at least in part on the weighted audience data, actual GRP values associated with the performance of the advertising schedule in the particular market;   generating a predicted GRP trend based on the actual GRP values; and   continually adjusting, using the processor, the advertising schedule to maintain the predicted GRP trend between the upper and lower boundary values.   
     
     
         2 . The method of  claim 1 , further comprising:
 determining the actual GRP values in real time.   
     
     
         3 . The method of  claim 1 , wherein determining the upper and lower boundary values further comprises:
 determining upper-inner and upper-outer boundaries; and   determining lower-inner and lower-outer boundaries.   
     
     
         4 . The method of  claim 3 , further comprising:
 adjusting the GRP trend by applying nudges to adjust actual GRP values falling between the upper-inner and lower-inner boundaries.   
     
     
         5 . The method of  claim 3 , further comprising:
 adjusting the GRP trend by applying corrections to adjust actual GRP values falling between either the upper-inner and upper-outer boundaries, or the lower-inner and lower-outer boundaries.   
     
     
         6 . The method of  claim 1 , further comprising:
 applying a first de-duplication weighting to audience data associated with audience members exposed to an advertisement less than a number of times corresponding to a saturation level; and   applying a second de-duplication weighting to audience data associated with audience members exposed to an advertisement less than the number of times corresponding to the saturation level.   
     
     
         7 . The method of  claim 1 , further comprising:
 determining a relative rating a plurality of spot breaks based on a predicted GRP associated with individual spot breaks; and   wherein continually adjusting the advertising schedule includes moving an advertisement from a first spot break to a second spot break based on the relative rating of the first and second spot breaks.   
     
     
         8 . A non-transitory computer readable medium tangibly embodying a program of computer executable instructions, the program of instructions comprising:
 at least one instruction to determine upper and lower boundary values based on estimated gross rating point (GRP) values associated with performance of an advertising schedule in a particular market;   at least one instruction to obtain audience data associated with the particular market;   at least one instruction to apply a de-duplication weighting to audience data to generate weighted audience data;   at least one instruction to determine, based at least in part on the weighted audience data, actual GRP values associated with the performance of the advertising schedule in the particular market;   at least one instruction to generate a predicted GRP trend based on the actual GRP values; and   at least one instruction to continually adjust the advertising schedule to maintain the predicted GRP trend between the upper and lower boundary values.   
     
     
         9 . The non-transitory computer readable medium of  claim 8 , further comprising:
 at least one instruction to determine the actual GRP values in real time.   
     
     
         10 . The non-transitory computer readable medium of  claim 8 , wherein at least one instruction to determine the upper and lower boundary values further comprises:
 at least one instruction to determine upper-inner and upper-outer boundaries; and   at least one instruction to determine lower-inner and lower-outer boundaries.   
     
     
         11 . The non-transitory computer readable medium of  claim 10 , further comprising:
 at least one instruction to adjust the GRP trend by applying nudges to adjust actual GRP values falling between the upper-inner and lower-inner boundaries.   
     
     
         12 . The non-transitory computer readable medium of  claim 10 , further comprising:
 at least one instruction to adjust the GRP trend by applying corrections to adjust actual GRP values falling between either the upper-inner and upper-outer boundaries, or the lower-inner and lower-outer boundaries.   
     
     
         13 . The non-transitory computer readable medium of  claim 8 , further comprising:
 at least one instruction to apply a first de-duplication weighting to audience data associated with audience members exposed to an advertisement less than a number of times corresponding to a saturation level; and   at least one instruction to apply a second de-duplication weighting to audience data associated with audience members exposed to an advertisement less than the number of times corresponding to the saturation level.   
     
     
         14 . The non-transitory computer readable medium of  claim 8 , further comprising:
 at least one instruction to determine a relative rating a plurality of spot breaks based on a predicted GRP associated with individual spot breaks; and   wherein the at least one instruction to continually adjust the advertising schedule includes at least one instruction to move an advertisement from a first spot break to a second spot break based on the relative rating of the first and second spot breaks.   
     
     
         15 . A system comprising:
 memory;   at least one processor operably coupled to said memory;   a program of computer readable instructions configured to be stored in the memory and executed by the processor, the program of instructions comprising:
 at least one instruction to determine upper and lower boundary values based on estimated gross rating point (GRP) values associated with performance of an advertising schedule in a particular market; 
 at least one instruction to obtain audience data associated with the particular market; 
 at least one instruction to apply a de-duplication weighting to audience data to generated weighted audience data; 
 at least one instruction to determine, based at least in part on the weighted audience data, actual GRP values associated with the performance of the advertising schedule in the particular market; 
 at least one instruction to generate a predicted GRP trend based on the actual GRP values; and 
 at least one instruction to continually adjust, using the processor, the advertising schedule to maintain the predicted GRP trend between the upper and lower boundary values. 
   
     
     
         16 . The system of  claim 15 , the program of instructions further comprising:
 at least one instruction to determine the actual GRP values in real time.   
     
     
         17 . The system of  claim 15 , the at least one instruction to determine the upper and lower boundary values further comprises:
 at least one instruction to determine upper-inner and upper-outer boundaries; and   at least one instruction to determine lower-inner and lower-outer boundaries.   
     
     
         18 . The system of  claim 17 , the program of instructions further comprising:
 at least one instruction to adjust the GRP trend by applying nudges to adjust actual GRP values falling between the upper-inner and lower-inner boundaries; and   at least one instruction to adjust the GRP trend by applying corrections to adjust actual GRP values falling between either the upper-inner and upper-outer boundaries, or the lower-inner and lower-outer boundaries.   
     
     
         19 . The system of  claim 15 , the program of instructions further comprising:
 at least one instruction to apply a first de-duplication weighting to audience data associated with audience members exposed to an advertisement less than a number of times corresponding to a saturation level; and   at least one instruction to apply a second de-duplication weighting to audience data associated with audience members exposed to an advertisement less than the number of times corresponding to the saturation level.   
     
     
         20 . The system of  claim 15 , the program of instructions further comprising:
 at least one instruction to determine a relative rating a plurality of spot breaks based on a predicted GRP associated with individual spot breaks; and   wherein the at least one instruction to continually adjust the advertising schedule includes at least one instruction to move an advertisement from a first spot break to a second spot break based on the relative rating of the first and second spot breaks.