Audience proposal creation and spot scheduling utilizing a framework for audience rating estimation

Abstract

A system determines a constraint associated with a pending deal for an advertiser based on target cost per thousand (CPM) reduction goal, demographics CPM cap, or established parameter. Rates are generated for each selling title for a week for a duration and a network of the pending deal. In certain time period for first channel of first network, buckets are determined based on sum of program attributes and time attributes for each second channel and weighing factor. Target audience rating estimates are acquired based on a predictive model, the buckets, the target CPM reduction goal, and the demographics CPM cap for plurality of networks. First proposal information is generated based on first distribution information of an audience spot and modified target CPM of a proposal associated with the pending deal based on target audience rating estimates. Audience spot is scheduled across the network for a selling title and week combination.

1 . (canceled) 
     
     
         2 . A computer-implemented method, comprising:
 determining, by one or more processors, a plurality of channel buckets for a target channel;   determining, by the one or more processors, a plurality of bucketized channel vectors for the target channel, wherein:
 (i) the plurality of bucketized channel vectors comprises a respective bucketized channel vector for each of the plurality of channel buckets, and 
 (ii) a bucketized channel vector of the plurality of bucketized channel vectors is based at least in part on a plurality of program attributes and time attributes for each of a plurality of channels within a channel bucket corresponding to the bucketized channel vector; 
   determining, by the one or more processors, a plurality of targeted audience rating estimates for the target channel based at least in part on the plurality of bucketized channel vectors; and   initiating, by the one or more processors, a scheduling of one or more audience spots for a pending deal based at least in part on the plurality of targeted audience rating estimates.   
     
     
         3 . The computer-implemented method of  claim 2 , wherein the bucketized channel vector is based at least in part on a sum of the plurality of program attributes and time attributes for each of the plurality of channels within the channel bucket. 
     
     
         4 . The computer-implemented method of  claim 2 , wherein the bucketized channel vector is based at least in part on one or more observed consumer behavior patterns. 
     
     
         5 . The computer-implemented method of  claim 2 , wherein each targeted audience rating estimate of the plurality of targeted audience rating estimates corresponds to a percentage of viewers that are engaged in a particular targeted activity. 
     
     
         6 . The computer-implemented method of  claim 2 , wherein the plurality of targeted audience rating estimates corresponds to a plurality of selling title-weeks across the target channel and one or more affiliated channels. 
     
     
         7 . The computer-implemented method of  claim 2 , further comprising:
 determining, by the one or more processors, a distribution model for the pending deal based on the plurality of targeted audience rating estimates; and   initiating, by the one or more processors, the scheduling of the one or more audience spots based at least in part on the distribution model.   
     
     
         8 . The computer-implemented method of  claim 7 , wherein the distribution model is generated based at least in part on a budget and a target cost per thousand (CPM) for the pending deal. 
     
     
         9 . The computer-implemented method of  claim 2 , wherein the plurality of time attributes is indicative of one or more of a quarter, seasonality, day of week, half hour, or holiday. 
     
     
         10 . The computer-implemented method of  claim 2 , wherein the plurality of program attributes is indicative of one or more of a genre, repeat, premiere, live, or duration. 
     
     
         11 . A computing system comprising memory and one or more processors communicatively coupled to the memory, the one or more processors configured to:
 determine a plurality of channel buckets for a target channel;   determine a plurality of bucketized channel vectors for the target channel, wherein:
 (i) the plurality of bucketized channel vectors comprises a respective bucketized channel vector for each of the plurality of channel buckets, and 
 (ii) a bucketized channel vector of the plurality of bucketized channel vectors is based at least in part on a plurality of program attributes and time attributes for each of a plurality of channels within a channel bucket corresponding to the bucketized channel vector; 
   determine a plurality of targeted audience rating estimates for the target channel based at least in part on the plurality of bucketized channel vectors; and   initiate a scheduling of one or more audience spots for a pending deal based at least in part on the plurality of targeted audience rating estimates.   
     
     
         12 . The computing system of  claim 11 , wherein the bucketized channel vector is based at least in part on a sum of the plurality of program attributes and time attributes for each of the plurality of channels within the channel bucket. 
     
     
         13 . The computing system of  claim 11 , wherein the bucketized channel vector is based at least in part on one or more observed consumer behavior patterns. 
     
     
         14 . The computing system of  claim 11 , wherein each targeted audience rating estimate of the plurality of targeted audience rating estimates corresponds to a percentage of viewers that are engaged in a particular targeted activity. 
     
     
         15 . The computing system of  claim 11 , wherein the plurality of targeted audience rating estimates corresponds to a plurality of selling title-weeks across the target channel and one or more affiliated channels. 
     
     
         16 . The computing system of  claim 11 , wherein the one or more processors are further configured to:
 determine a distribution model for the pending deal based on the plurality of targeted audience rating estimates; and   initiate the scheduling of the one or more audience spots based at least in part on the distribution model.   
     
     
         17 . One or more non-transitory computer-readable storage media including instructions that, when executed by one or more processors, cause the one or more processors to:
 determine a plurality of channel buckets for a target channel;   determine a plurality of bucketized channel vectors for the target channel, wherein:
 (i) the plurality of bucketized channel vectors comprises a respective bucketized channel vector for each of the plurality of channel buckets, and 
 (ii) a bucketized channel vector of the plurality of bucketized channel vectors is based at least in part on a plurality of program attributes and time attributes for each of a plurality of channels within a channel bucket corresponding to the bucketized channel vector; 
   determine a plurality of targeted audience rating estimates for the target channel based at least in part on the plurality of bucketized channel vectors; and   initiate a scheduling of one or more audience spots for a pending deal based at least in part on the plurality of targeted audience rating estimates.   
     
     
         18 . The one or more non-transitory computer-readable storage media of  claim 17 , wherein the instructions further cause the one or more processors to:
 determine a distribution model for the pending deal based on the plurality of targeted audience rating estimates; and   initiate the scheduling of the one or more audience spots based at least in part on the distribution model.   
     
     
         19 . The one or more non-transitory computer-readable storage media of  claim 18 , wherein the distribution model is generated based at least in part on a budget and a target cost per thousand (CPM) for the pending deal. 
     
     
         20 . The one or more non-transitory computer-readable storage media of  claim 17 , wherein the plurality of time attributes is indicative of one or more of a quarter, seasonality, day of week, half hour, or holiday. 
     
     
         21 . The one or more non-transitory computer-readable storage media of  claim 17 , wherein the plurality of program attributes is indicative of one or more of a genre, repeat, premiere, live, or duration.