System and method for targeting advertisements

1. A system comprising:

a data aggregator comprising at least one database server;

a memory operable to store at least one program; and

at least one processor communicatively coupled to the memory, in which the at least one program, when executed by the at least one processor, causes the at least one processor to:

receive target browsing characteristic data describing media consumer characteristics targeted by an advertiser wherein target browsing characteristics included in the received data are selected by the advertiser;

determine, at least from the received target browsing characteristic data, a first set of a plurality of user keys associated with one or more media consumers exhibiting the target browsing characteristic data linked with at least one media consuming behavior;

determine a first count of users included in the first set;

determine a second count of a total number of users whose data is contained in one or more databases of the data aggregator;

determine a media target list, the media target list comprising a second set of a plurality of user keys associated with one or more users exhibiting a first media consuming behavior;

determine a third count of users included in the second set;

identify the user keys in the first set that match the user keys in the second set;

determine a fourth count of a number of user keys in the first set that match the user keys in the second set;

determine a first index value based at least in part on a ratio between an incidence of the target browsing characteristic in the media. target list and an incidence of the target browsing characteristic among users whose data is contained in the one or more data aggregator databases based on the first count, second count, third count and fourth count, wherein the first index value facilitates performing a comparison of a relative measure of targeting a particular set of users, with the target browsing characteristic, based at least in part on an index value determination of respective index values corresponding to a defined value applied to media consuming behavior connected to a media; and

generate a table providing at least a list of media consumers associated with the media consuming behavior and within at least the first count, the second count, the third count, and the fourth count.

2. The system of claim 1 , wherein the at least one program, when executed by the at least one processor, further causes the at least one processor to:

determine a second media target list, the second media target list comprising a respective set of one or more user keys associated with respective one or more users exhibiting a second media consuming behavior, wherein the second media consuming behavior is different than the first media consuming behavior;

determine a second index value based at least in part on a respective ratio between a respective incidence of the target browsing characteristic in the second media target list and the incidence of the target characteristic among users whose data is contained in the one or more databases based on the first count, second count, third count and fourth count;

determine a ranking of the first index value and the second index value; and

generate a table including at least the first index value and the second index value based at least in part on the ranking, wherein the table is utilized for performing the comparison of the relative measure of targeting the particular set of users, with the target characteristic, among at least one media outlet.

3. The system of claim I, wherein each of the respective index values is based at least in part on the particular set of users that are associated with particular consumer characteristics included in the target browsing characteristic data for a respective media outlet.

4. The system of claim I. wherein the first index is based on a logarithm of the ratio between the incidence of the target browsing characteristic in the media target list and. the incidence of the target characteristic among users whose data is contained in the one or more databases based on the first count, second count, third count and fourth count.

5. A non-transitory computer-readable storage medium that stores instructions which, when executed by one or more processors, cause the one or more processors to perform a method comprising:

receive target browsing characteristic data describing media consumer characteristics targeted by an advertiser wherein target browsing characteristics included in the received data are selected by the advertiser;

determine, at least from the received target browsing characteristic data, a first set of a plurality of user keys associated with one or more media consumers exhibiting the target browsing characteristic data linked with at least one media consuming behavior;

determine a first count of users included in the first set;

determine a second count of a total number of users whose data is contained in one or more databases of a data aggregator;

determine a media target list, the media target list comprising a second set of a plurality of user keys associated with one or more users exhibiting a first media consuming behavior;

determine a third count of users included in the second set;

identify the user keys in the first set that match the user keys in the second set;

determine a fourth count of a number of user keys in the first set that match the user keys in the second set;

determine a first index value based at least in part on a ratio between an incidence of the target browsing characteristic in the media. target list and an incidence of the target browsing characteristic among users whose data is contained in the one or more data aggregator databases based on the first count, second count, third count and fourth count, wherein the first index value facilitates performing a comparison of a relative measure of targeting a particular set of users, with the target browsing characteristic, based at least in part on an index value determination of respective index values corresponding to a defined value applied to media consuming behavior connected to a media; and

generate a table providing at least a list of media consumers associated with the media consuming behavior and within at least the first count, the second count, the third count, and the fourth count.

6. The medium of claim 5 , wherein the instructions, when executed by the at least one processor, further causes the at least one processor to:

determine a second media target list, the second media target list comprising a respective set of one or more user keys associated with respective one or more users exhibiting a second media consuming behavior, wherein the second media consuming behavior is different than the first media consuming behavior;

determine a second index value based at least in part on a respective ratio between a respective incidence of the target browsing characteristic in the second media target list and the incidence of the target characteristic among users whose data is contained in the one or more databases based on the first count, second count, third count and fourth count;

determine a ranking of the first index value and the second index value; and

generate a table including at least the first index value and the second index value based at least in part on the ranking, wherein the table is utilized for performing the comparison of the relative measure of targeting the particular set of users, with the target characteristic, among at least one media outlet.

7. The medium of claim 5 , wherein each of the respective index values is based at least in part on the particular set of users that are associated with particular consumer characteristics included in the target browsing characteristic data for a respective media outlet.

8. The medium of claim 5 , wherein the first index is based on a logarithm of the ratio between the incidence of the target browsing characteristic in the media target list and the incidence of the target characteristic among users whose data is contained in the one or more databases based on the first count, second count, third count, and fourth count.

9. A computer-implemented method, comprising:

receiving target browsing characteristic data describing media consumer characteristics targeted by an advertiser wherein target browsing characteristics included in the received data are selected by the advertiser;

determining, at least from the received target browsing characteristic data, a first set of a plurality of user keys associated with one or more media consumers exhibiting the target browsing characteristic data linked with at least one media consuming behavior;

determining a first count of users included in the first set;

determining a second count of a total number of users whose data is contained in one or more databases of a data aggregator;

determining a media target list, the media target list comprising a second set of a plurality of user keys associated with one or more users exhibiting a first media consuming behavior;

determining a third count of users included in the second set;

identifying the user keys in the first set that match the user keys in the second set;

determining a fourth count of a number of user keys in the first set that match the user keys in the second set;

determining a first index value based at least in part on a ratio between an incidence of the target browsing characteristic in the media target list and an incidence of the target browsing characteristic among users whose data is contained in the one or more data aggregator databases based on the first count, second count, third count and fourth count, wherein the first index value facilitates performing a comparison of a relative measure of targeting a particular set of users, with the target browsing characteristic, based at least in part on an index value determination of respective index values corresponding to a defined value applied to media consuming behavior connected to a media; and

generating a table providing at least a list of media consumers associated with the media consuming behavior and within at least the first count, the second count, the third count, and the fourth count.

10. The method of claim 9 , further comprising:

determining a second media target list, the second media target list comprising a respective set of one or more user keys associated with respective one or more users exhibiting a second media consuming behavior, wherein the second media consuming behavior is different than the first media consuming behavior;

determining a second index value based at least in part on a respective ratio between a respective incidence of the target browsing characteristic in the second media target list and the incidence of the target characteristic among users whose data is contained in the one or more databases based on the first count, second count, third count and fourth count;

determining a ranking of the first index value and the second index value; and

generating a table including at least the first index value and the second index value based at least in part on the ranking, wherein the table is utilized for performing the comparison of the relative measure of targeting the particular set of users, with the target characteristic, among at least one media outlet.

11. The method of claim 9 , wherein each of the respective index values is based at least in part on the particular set of users that are associated with particular consumer characteristics included in the target browsing characteristic data for a respective media outlet.

12. The method of claim 9 , wherein the first index is based on a logarithm of the ratio between the incidence of the target browsing characteristic in the media target list and the incidence of the target characteristic among users whose data is contained in the one or more databases based on the first count, second count, third count and fourth count.