Methods and apparatus to calculate granular data of a region based on another region for media audience measurement
Methods and apparatus to calculate granular data of a region based on another region for media audience measurement are disclosed. An example method for calculating, via a processor, granular data of a region includes determining aggregate behavioral data associated with a media audience measurement of a target region. The example method includes determining, via the processor, aggregate demographics data of the target region. The example method includes determining, via the processor, granular data of a source region. The example method includes calculating, via the processor, granular data of the target region to measure a media audience of the target region by apportioning the aggregate demographics data and the aggregate behavioral data of the target region based on the granular data of the source region.
1. An apparatus to determine an audience count of a target region, the apparatus comprising:
a target region determiner to:
determine aggregate behavioral data associated with media audience measurement of the target region, the aggregate behavioral data satisfying a behavioral constraint, the behavioral constraint corresponding to exposure to a media event; and
determine aggregate demographics data of the target region, the aggregate demographics data associated with a first demographic constraint and a second demographic constraint;
a source region determiner to determine granular data of a source region, the granular data including first source region members that satisfy the behavioral constraint and the first demographic constraint and second source region members that satisfy the behavioral constraint and the second demographic constraint; and
a target region calculator to determine the audience count of the media event in the target region by apportioning the aggregate behavioral data among the first demographic constraint and the second demographic constraint, the apportioning based on (a) the aggregate demographics data of the target region and (b) the granular data of the source region.
2. The apparatus as defined in claim 1 , wherein the target region calculator is to determine the audience count of the media event in the target region based on a first weight corresponding to a value of the first demographic constraint and a second weight corresponding to a value of the second demographic constraint.
3. The apparatus as defined in claim 1 , further including:
a linear identifier to determine if there is a linear relationship between the aggregate demographics data and the aggregate behavioral data;
a linear calculator to calculate, in response to determining the linear relationship, the audience count of the media event of the target region based on the linear relationship; and
a non-linear calculator to calculate, in response to determining no linear relationship, the audience count of the media event of the target region by performing non-linear optimization based on the granular data, the aggregate demographics data, and the aggregate behavioral data.
4. The apparatus as defined in claim 3 , wherein the non-linear calculator is to define an optimization constraint based on the aggregate behavioral data and the aggregate demographics data, the non-linear optimization being limited by the optimization constraint.
5. The apparatus as defined in claim 3 , wherein the non-linear calculator is to calculate an optimization parameter that indicates a variance based on the granular data of the source region and the audience count of the target region.
6. The apparatus as defined in claim 1 , wherein the source region includes panelist households and the target region does not include panelists households, the source region determiner to determine the granular data based on exposure data from the panelist households.
7. The apparatus as defined in claim 1 , wherein the first demographic constraint and the second demographic constraint are mutually exclusive.
8. A non-transitory computer readable storage medium comprising instructions which, when executed, cause a processor to at least:
determine aggregate behavioral data associated with media audience measurement of a target region, the aggregate behavioral data satisfying a behavioral constraint, the behavioral constraint corresponding to exposure to a media event; and
determine aggregate demographics data of the target region, the aggregate demographics data associated with a first demographic constraint and a second demographic constraint;
determine granular data of a source region, the granular data including first source region members that satisfy the behavioral constraint and the first demographic constraint and second source region members that satisfy the behavioral constraint and the second demographic constraint; and
determine an audience count of the media event in the target region by apportioning the aggregate behavioral data among the first demographic constraint and the second demographic constraint, the apportioning based on (a) the aggregate demographics data of the target region and (b) the granular data of the source region.
9. The non-transitory computer readable storage medium as defined in claim 8 , wherein the instructions cause the processor to determine the audience count of the media event in the target region based on a first weight corresponding to a value of the first demographic constraint and a second weight corresponding to a value of the second demographic constraint.
10. The non-transitory computer readable storage medium as defined in claim 8 , wherein the instructions further cause the processor to:
determine if there is a linear relationship between the aggregate demographics data and the aggregate behavioral data;
calculate, in response to determining the linear relationship, the audience count of the media event of the target region based on the linear relationship; and
calculate, in response to determining no linear relationship, the audience count of the media event of the target region by performing non-linear optimization based on the granular data, the aggregate demographics data, and the aggregate behavioral data.
11. The non-transitory computer readable storage medium as defined in claim 10 , wherein the instructions further cause the processor to define an optimization constraint based on the aggregate behavioral data and the aggregate demographics data, the non-linear optimization being limited by the optimization constraint.
12. The non-transitory computer readable storage medium as defined in claim 10 , wherein the instructions further cause the processor to calculate an optimization parameter that indicates a variance based on the granular data of the source region and the audience count of the target region.
13. The non-transitory computer readable storage medium as defined in claim 8 , wherein the source region includes panelist households and the target region does not include panelists households, and the instructions further cause the processor to determine the granular data based on exposure data from the panelist households.
14. The non-transitory computer readable storage medium as defined in claim 8 , wherein the first demographic constraint and the second demographic constraint are mutually exclusive.
15. A method to determine an audience count of a target region, the method comprising:
determining aggregate behavioral data associated with media audience measurement of the target region, the aggregate behavioral data satisfying a behavioral constraint, the behavioral constraint corresponding to exposure to a media event; and
determining aggregate demographics data of the target region, the aggregate demographics data associated with a first demographic constraint and a second demographic constraint;
determining granular data of a source region, the granular data including first source region members that satisfy the behavioral constraint and the first demographic constraint and second source region members that satisfy the behavioral constraint and the second demographic constraint; and
determining the audience count of the media event in the target region by apportioning the aggregate behavioral data among the first demographic constraint and the second demographic constraint, the apportioning based on (a) the aggregate demographics data of the target region and (b) the granular data of the source region.
16. The method as defined in claim 15 , wherein determining the audience count of the media event in the target region is further based on a first weight corresponding to a value of the first demographic constraint and a second weight corresponding to a value of the second demographic constraint.
17. The method as defined in claim 15 , further including:
determining if there is a linear relationship between the aggregate demographics data and the aggregate behavioral data;
calculating, in response to determining the linear relationship, the audience count of the media event of the target region based on the linear relationship; and
calculating, in response to determining no linear relationship, the audience of the media event of the target region by performing non-linear optimization based on the granular data, the aggregate demographics data, and the aggregate behavioral data.
18. The method as defined in claim 17 , further including defining an optimization constraint based on the aggregate behavioral data and the aggregate demographics data, the non-linear optimization being limited by the optimization constraint.
19. The method as defined in claim 17 , further including calculating an optimization parameter that indicates a variance based on the granular data of the source region and the audience count of the target region.
20. The method as defined in claim 15 , wherein the source region includes panelist households and the target region does not include panelists households, and further including determining the granular data based on exposure data from the panelist households.