SYSTEMS AND METHODS FOR OPTIMIZING DATA DRIVEN MEDIA PLACEMENT
System and methods are presented for selecting advertising slots in an advertising campaign with an audience management system. In some embodiments, a user selects a budget value, which is partitioned into a first and second partition value. The audience management module stores a plurality of data structures in a memory, and defines a plurality of groups such that each of the plurality of data structures is associated with one of the plurality of groups. A portion of the first partition value is allocated to each of the plurality of groups, and the audience management module flags, for each group, at least one data structure based on the portion of the first partition value allocated to the group. The audience management module identifies a subset of unflagged data structures, and flags at least one data structure based on the second partition value.
1 . A method for selecting advertising slots in an advertising campaign, the method comprising:
receiving a user selection of a budget value;
storing the budget value in a memory;
partitioning the budget value into a first partition value and a second partition value, wherein each of the first and second partition values is stored in the memory;
storing a plurality of data structures in the memory;
defining a plurality of groups, wherein each of the plurality of data structures is associated with one of the plurality of groups;
allocating a portion of the first partition value to each of the plurality of groups;
flagging, for each of the plurality of groups, at least one data structure associated with the group based on the portion of the first partition value allocated to the group;
identifying a subset of unflagged data structures within the plurality of data structures; and
flagging at least one data structure within the subset based on the second partition value.
2 . The method of claim 1 , wherein flagging, for each of the plurality of groups, at least one data structure associated with the group based on the portion of the first partition value allocated to the group comprises:
ranking, based on an audience-related criterion, each data structure associated with the group;
identifying a plurality of ranked data structures having the highest rankings of each data structure associated with the group; and
flagging each of the identified plurality of ranked data structures, wherein a sum of budget weights associated with each of the identified plurality of ranked data structures is less than or equal to the portion of the first partition value allocated to the group.
3 . The method of claim 1 , wherein flagging at least one data structure within the subset based on the second partition value comprises:
ranking, based on an audience-related criterion, each unflagged data structure of the plurality of data structures;
identifying a plurality of ranked data structures having the highest rankings of each data structure of the plurality of data structures; and
flagging each of the identified plurality of ranked data structures, wherein a sum of budget weights associated with each of the identified plurality of ranked data structures is less than or equal to the second partition value.
4 . The method of claim 1 , wherein allocating a portion of the first partition value to each of the plurality of groups comprises allocating a portion of the first partition value equally to each of the plurality of groups.
5 . The method of claim 1 , wherein each of the plurality of groups is representative of a time period.
6 . The method of claim 1 , wherein each of the plurality of data structures is representative of an available advertising slot.
7 . The method of claim 1 , wherein flagging a data structure is indicative of adding an available advertising slot to an advertising campaign plan.
8 . The method of claim 1 , wherein the first partition value and the second partition value are user-designated.
9 . The method of claim 1 , further comprising generating for display a plurality of cells in a grid arrangement, wherein:
each of the plurality of cells is representative of one of the plurality of data structures, and
each of the plurality of cells is arranged according to a content source and a time period of the data structure represented by the cell.
10 . The method of claim 1 , wherein each of the plurality of data structures is associated with a budget weight, and wherein each budget weight is determined based on a pricing tier.
11 . A system for selecting advertising slots in an advertising campaign, the system comprising:
processing circuitry, wherein the processing circuitry is configured to:
receive a user selection of a budget value;
store the budget value in a memory;
partition the budget value into a first partition value and a second partition value, wherein each of the first and second partition values is stored in the memory;
store a plurality of data structures in the memory;
define a plurality of groups, wherein each of the plurality of data structures is associated with one of the plurality of groups;
allocate a portion of the first partition value to each of the plurality of groups;
flag, for each of the plurality of groups, at least one data structure associated with the group based on the portion of the first partition value allocated to the group;
identify a subset of unflagged data structures within the plurality of data structures; and
flag at least one data structure within the subset based on the second partition value.
12 . The system of claim 11 , wherein the processing circuitry is further configured to:
rank, based on an audience-related criterion, each data structure associated with the group;
identify a plurality of ranked data structures having the highest rankings of each data structure associated with the group; and
flag each of the identified plurality of ranked data structures, wherein a sum of budget weights associated with each of the identified plurality of ranked data structures is less than or equal to the portion of the first partition value allocated to the group.
13 . The system of claim 11 , wherein the processing circuitry is further configured to:
rank, based on an audience-related criterion, each unflagged data structure of the plurality of data structures;
identify a plurality of ranked data structures having the highest rankings of each data structure of the plurality of data structures; and
flag each of the identified plurality of ranked data structures, wherein a sum of budget weights associated with each of the identified plurality of ranked data structures is less than or equal to the second partition value.
14 . The system of claim 11 , wherein the processing circuitry is further configured to allocate a portion of the first partition value equally to each of the plurality of groups.
15 . The system of claim 11 , wherein each of the plurality of groups is representative of a time period.
16 . The system of claim 11 , wherein each of the plurality of data structures is representative of an available advertising slot.
17 . The system of claim 11 , wherein flagging a data structure is indicative of adding an available advertising slot to an advertising campaign plan.
18 . The system of claim 11 , wherein the first partition value and the second partition value are user-designated.
19 . The system of claim 11 , wherein the processing circuitry is further configured to generate for display a plurality of cells in a grid arrangement, wherein:
each of the plurality of cells is representative of one of the plurality of data structures, and
each of the plurality of cells is arranged according to a content source and a time period of the data structure represented by the cell.
20 . The system of claim 11 , wherein each of the plurality of data structures is associated with a budget weight, and wherein each budget weight is determined based on a pricing tier.
21 - 60 . (canceled)