DEMAND SEGMENTATION AND FORECASTING FOR MEDIA INVENTORY ALLOCATION
Forecasted attributes may be determined for scheduled media items based at least in part on observed characteristics associated with previously presented media items. A division of the scheduled media items into a plurality of media segments may be identified based on the forecasted attributes. A media allocation plan may be determined by solving an optimization problem that includes the media segments and the forecasted attributes.
1 . A method comprising:
receiving from one or more remote computing systems via a network interface scheduling information for a plurality of scheduled media items, the scheduled media items including one or more television or radio programs, each of the scheduled media items being scheduled for presentation on a respective communication channel at a respective date and time;
determining a plurality of forecasted media item attributes, each of the forecasted media item attributes predicting an audience characteristic for a respective one or more of the plurality of scheduled media items, each of the forecasted attributes being determined based at least in part on a plurality of observed characteristics associated with previously presented media items;
identifying a division of the scheduled media items into a plurality of media segments based on the forecasted attributes, a designated one of the plurality of media segments including two or more of the scheduled media items identified based on similarities among their forecasted attributes;
determining a plurality of forecasted media segment attributes, each of the forecasted media segment attributes predicting a characteristic for a respective one of the plurality of media segments, the plurality of forecasted media segment attributes including a plurality of viewership composition values, each viewership composition value identifying a predicted audience attribute for a respective one of the plurality of media segments;
determining via a processor a media allocation plan by solving an optimization problem that includes the media segments and the forecasted media segment attributes and that is specified as a linear programming problem or a mixed-integer programming problem, the media allocation plan identifying an allocation of a plurality of advertisements to a subset of the media segments; and
storing the media allocation plan on a storage device.
2 . The method recited in claim 1 , wherein the optimization problem also includes one or more allocation constraints, each allocation constraint restricting the allocation of advertisements to the scheduled media items.
3 . The method recited in claim 2 , wherein a designated one of the allocation constraints is a time constraint, the time constraint restricting presentation of a designated advertisement based on a time of day.
4 . The method recited in claim 2 , wherein a designated one of the allocation constraints is a device constraint, the device constraint restricting presentation of a designated one of the advertisements based on a type of device on which the designated advertisement is presented.
5 . The method recited in claim 1 , wherein one or more of the forecasted attributes also correspond to a respective one or more of a plurality of advertising entities, each advertising entity corresponding to a respective one or more of the plurality of advertisements.
6 . The method recited in claim 1 , wherein the optimization problem is a linear programming problem.
7 . The method recited in claim 1 , wherein the optimization problem is a mixed-integer programming problem.
8 . The method recited in claim 1 , wherein the media allocation plan includes a respective media segment magnitude for each or selected ones of the subset of the media segments, the respective media segment magnitude identifying a number of advertisement opportunities associated with the respective media segment.
9 . The method recited in claim 1 , wherein the forecasted attributes include one or more attributes of a respective anticipated audience of the respective one or more scheduled media items.
10 . The method recited in claim 1 , wherein the forecasted attributes include one or more attributes of devices on which the scheduled media items are anticipated to be accessed.
11 . The method recited in claim 1 , wherein the forecasted attributes include one or more attributes of web pages on which the scheduled media items are anticipated to be accessed.
12 . A computing system comprising:
a communication interface operable to receive from one or more remote computing systems via a network interface scheduling information for a plurality of scheduled media items, the scheduled media items including one or more television or radio programs, each of the scheduled media items being scheduled for presentation on a respective communication channel at a respective date and time;
a processor operable to:
determine a plurality of forecasted media item attributes, each of the forecasted media item attributes predicting an audience characteristic for a respective one or more of the plurality of scheduled media items, each of the forecasted attributes being determined based at least in part on a plurality of observed characteristics associated with previously presented media items;
identify a division of the scheduled media items into a plurality of media segments based on the forecasted attributes, a designated one of the plurality of media segments including two or more of the scheduled media items identified based on similarities among their forecasted attributes;
determine a plurality of forecasted media segment attributes, each of the forecasted media segment attributes predicting a characteristic for a respective one of the plurality of media segments, the plurality of forecasted media segment attributes including a plurality of viewership composition values, each viewership composition value identifying a predicted audience attribute for a respective one of the plurality of media segments;
determine via a processor a media allocation plan by solving an optimization problem that includes the media segments and the forecasted media segment attributes and that is specified as a linear programming problem or a mixed-integer programming problem, the media allocation plan identifying an allocation of a plurality of advertisements to a subset of the media segments; and
a storage system operable to store the media allocation plan.
13 . The computing system recited in claim 12 , wherein the optimization problem also includes one or more allocation constraints, each allocation constraint restricting the allocation of advertisements to the scheduled media items.
14 . The computing system recited in claim 13 , wherein a designated one of the allocation constraints is a time constraint, the time constraint restricting presentation of a designated advertisement based on a time of day.
15 . The computing system recited in claim 13 , wherein a designated one of the allocation constraints is a device constraint, the device constraint restricting presentation of a designated one of the advertisements based on a type of device on which the designated advertisement is presented.
16 . The computing system recited in claim 12 , wherein one or more of the forecasted attributes also correspond to a respective one or more of a plurality of advertising entities, each advertising entity corresponding to a respective one or more of the plurality of advertisements.
17 . One or more non-transitory computer readable media having instructions stored thereon for performing a method, the method comprising:
receiving from one or more remote computing systems via a network interface scheduling information for a plurality of scheduled media items, the scheduled media items including one or more television or radio programs, each of the scheduled media items being scheduled for presentation on a respective communication channel at a respective date and time;
determining a plurality of forecasted media item attributes, each of the forecasted media item attributes predicting an audience characteristic for a respective one or more of the plurality of scheduled media items, each of the forecasted attributes being determined based at least in part on a plurality of observed characteristics associated with previously presented media items;
identifying a division of the scheduled media items into a plurality of media segments based on the forecasted attributes, a designated one of the plurality of media segments including two or more of the scheduled media items identified based on similarities among their forecasted attributes;
determining a plurality of forecasted media segment attributes, each of the forecasted media segment attributes predicting a characteristic for a respective one of the plurality of media segments, the plurality of forecasted media segment attributes including a plurality of viewership composition values, each viewership composition value identifying a predicted audience attribute for a respective one of the plurality of media segments;
determining via a processor a media allocation plan by solving an optimization problem that includes the media segments and the forecasted media segment attributes and that is specified as a linear programming problem or a mixed-integer programming problem, the media allocation plan identifying an allocation of a plurality of advertisements to a subset of the media segments; and
storing the media allocation plan on a storage device.
18 . The one or more non-transitory computer readable media recited in claim 17 , wherein the optimization problem also includes one or more allocation constraints, each allocation constraint restricting the allocation of advertisements to the scheduled media items.
19 . The one or more non-transitory computer readable media recited in claim 18 , wherein a designated one of the allocation constraints is a time constraint, the time constraint restricting presentation of a designated advertisement based on a time of day.
20 . The one or more non-transitory computer readable media recited in claim 18 , wherein a designated one of the allocation constraints is a device constraint, the device constraint restricting presentation of a designated one of the advertisements based on a type of device on which the designated advertisement is presented.