CALCULATING AUDIENCE METRICS FOR ONLINE CAMPAIGNS

• US 20140108130A1
• Filed: 11/09/2012
• Published: 04/17/2014
• Est. Priority Date: 10/12/2012
• Status: Abandoned Application

• Current Assignee: Google Inc. (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Koehler, James R., Vos, Wiesner J., Skvortsov, Evgeny, Rutishauser, Lukas
• Application Number:
  US13/672,780
• Publication Number:
  US 20140108130A1
• Time in Patent Office: Days
• US Class Current: 705/14.45
• CPC Class Codes: G06Q 30/0246 Traffic

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer-readable storage medium, for determining performance for a campaign. A method includes: identifying a campaign associated with the delivery of an electronic media item; identifying identifiers of devices that were served impressions of the electronic media item; determining a number of unique identifiers that received impressions and a number of views of the electronic media item per identifier; identifying a plurality of demographic categories; identifying labeled identifiers; determining a number of identifiers and views per demographic category for the campaign; accumulating un-labeled identifiers to produce a count of un-labeled identifiers and views; determining, for the labeled identifiers, a distribution across the plurality of demographic categories; adjusting for errors in the determined distribution; determining an overall distribution among the demographic categories for impressions; and applying the overall distribution to a total number of unique identifiers and views for the campaign.

Claims

1. A method comprising:

identifying a campaign associated with the delivery of an electronic media item over an online network;

identifying data associated with impressions of electronic media items over the online network, each entry in the data including an identifier associated with a requesting device that was served a given impression;

determining a number of unique identifiers that received impressions of the electronic media item and a number of views of the electronic media item per identifier;

identifying a plurality of demographic categories;

identifying, from the unique identifiers, labeled identifiers, wherein a labeled identifier is able to be resolved to a particular user that has known demographic characteristics;

using the labeled identifiers, determining a number of identifiers and views per demographic category for the campaign;

accumulating the un-labeled identifiers to produce a count of un-labeled identifiers and views;

determining, for the labeled identifiers, a distribution across the plurality of demographic categories;

adjusting for errors in the determined distribution including compensating for a first error factor associated with a known error bias in the number of labeled identifiers and a second error factor associated with an underrepresentation of any group in the demographic characteristics;

determining an overall distribution among the demographic categories for impressions using the determined distribution and the first and second error factors; and

applying the overall distribution to a total number of unique identifiers and views including applying the overall distribution to the un-labeled identifiers to determine the overall distribution of identifiers and views per demographic category for the campaign.

2. The method of claim 1 wherein the identifiers are cookies.

3. The method of claim 1 further comprising determining a number of people that viewed the electronic media item in a given demographic category based at least in part on the total number of unique identifiers.

4. The method of claim 3 further comprising determining a GRP (Gross Rating Point) for the campaign for a demographic category as the number of people times the number of views in the demographic category divided by a total number of people available in the demographic category in a given region.

5. The method of claim 4 wherein the region is a country.

6. The method of claim 1 wherein the electronic media item is an advertisement.

7. The method of claim 1 wherein the distribution is defined by a vector X, wherein the i-th component of X is the fraction of labeled identifiers in the i-th demographic category.

8. The method of claim 7 further comprising determining an alpha-value for the campaign, where the alpha-value represents a fraction of labeled identifiers to unlabeled identifiers;

and using the alpha-value when adjusting for errors.

9. The method of claim 8 wherein adjusting for errors includes determining a Y, where Y=alpha-value*AX+(1−

alpha-value)*BX/|BX|, where A and B are predetermined matrices.

10. The method of claim 9 wherein determining an overall distribution among the demographic categories for impressions further includes extrapolating demographic identifier distribution to all identifiers including multiplying Y by the number of unique identifiers for the campaign.

11. The method of claim 1 wherein adjusting for errors further includes adjusting to compensate for errors in assigning users labels that are in the data.

12. The method of claim 1 wherein adjusting for errors further includes adjusting for bias in a labeling methodology used to label users.

13. The method of claim 1 wherein adjusting for errors further includes adjusting for underrepresentation of a demographic group in the demographic categories based at least in part on the labels.

14. The method of claim 1 wherein determining the number of unique identifiers that received impressions of the electronic media item is based at least in part on a calibration panel.

15. The method of claim 14 wherein the second error factor compensates for demographic bias in the calibration panel.

16. The method of claim 1 wherein the data is log data.

17. A computer program product tangibly embodied in a computer-readable storage device and comprising instructions that, when executed by a processor, cause the processor to:

identify a campaign associated with the delivery of an electronic media item over an online network;

identify data associated with impressions of electronic media items over the online network, each entry in the data including an identifier associated with a requesting device that was served a given impression;

determine a number of unique identifiers that received impressions of the electronic media item and a number of views of the electronic media item per identifier;

identify a plurality of demographic categories;

identify, from the unique identifiers, labeled identifiers, wherein a labeled identifier is able to be resolved to a particular user that has known demographic characteristics;

use the labeled identifiers to determine a number of identifiers and views per demographic category for the campaign;

accumulate the un-labeled identifiers to produce a count of un-labeled identifiers and views;

determine, for the labeled identifiers, a distribution across the plurality of demographic categories;

adjust for errors in the determined distribution including compensating for a first error factor associated with a known error bias in the number of labeled identifiers and a second error factor associated with an underrepresentation of any group in the demographic characteristics;

determine an overall distribution among the demographic categories for impressions using the determined distribution and the first and second error factors; and

apply the overall distribution to a total number of unique identifiers and views including applying the overall distribution to the un-labeled identifiers to determine the overall distribution of identifiers and views per demographic category for the campaign.

18. The product of claim 17 wherein the identifiers are cookies.

19. The product of claim 17 further comprising instructions that, when executed by the processor, cause the processor to determine a number of people that viewed the electronic media item in a given demographic category based at least in part on the total number of unique identifiers.

20. The product of claim 17 further comprising instructions that, when executed by the processor, cause the processor to determine a GRP (Gross Rating Point) for the campaign for a demographic category as the number of people times the number of views in the demographic category divided by a total number of people available in the demographic category in a given region.

21. A system comprising:

a content management system;

log data; and

panel data;

wherein the content management system is configured to;

identify a campaign associated with the delivery of an electronic media item over an online network;

identify, from the log data, data associated with impressions of electronic media items over the online network, each entry in the data including an identifier associated with a requesting device that was served a given impression;

determine a number of unique identifiers that received impressions of the electronic media item and a number of views of the electronic media item per identifier;

identify a plurality of demographic categories;

identify, from the unique identifiers, labeled identifiers, wherein a labeled identifier is able to be resolved to a particular user that has known demographic characteristics;

use the labeled identifiers to determine a number of identifiers and views per demographic category for the campaign;

accumulate the un-labeled identifiers to produce a count of un-labeled identifiers and views;

determine, for the labeled identifiers, a distribution across the plurality of demographic categories;

using the panel data, adjust for errors in the determined distribution including compensating for a first error factor associated with a known error bias in the number of labeled identifiers and a second error factor associated with an underrepresentation of any group in the demographic characteristics;

determine an overall distribution among the demographic categories for impressions using the determined distribution and the first and second error factors; and

apply the overall distribution to a total number of unique identifiers and views including applying the overall distribution to the un-labeled identifiers to determine the overall distribution of identifiers and views per demographic category for the campaign.

22. The system of claim 21 wherein the identifiers are cookies.

23. The system of claim 21 wherein the content management system is configured to determine a number of people that viewed the electronic media item in a given demographic category based at least in part on the total number of unique identifiers.

24. The system of claim 21 wherein the content management system is configured to determine a GRP (Gross Rating Point) for the campaign for a demographic category as the number of people times the number of views in the demographic category divided by a total number of people available in the demographic category in a given region.