MEASURING ADVERTISING EFFECTIVENESS WITHOUT CONTROL GROUP

• US 20110137721A1
• Filed: 12/03/2010
• Published: 06/09/2011
• Est. Priority Date: 12/03/2009
• Status: Abandoned Application

• Current Assignee: comScore, Inc.
• Original Assignee: comScore, Inc.
• Inventors: Bansal, Harvir Singh
• Application Number:
  US12/959,878
• Publication Number:
  US 20110137721A1
• Time in Patent Office: Days
• US Class Current: 705/14.41
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements

Abstract

Measurement data is accessed. The measurement data is associated with a group of users that have been exposed to at least one advertising creative that is part of an advertising campaign. The measurement data reflects one or more consumer responses and one or more non-zero exposure levels. The non-zero exposure levels correspond to non-zero amounts of exposures to at least one advertising creative that is part of the advertising campaign. A model that relates consumer response measures to one or more exposure levels is generated based on the accessed measurement data. Based on the generated model, a consumer response measure for a zero exposure level is determined. The zero exposure level corresponds to a zero amount of exposures to at least one advertising creative that is part of the advertising campaign. An advertising effectiveness metric is determined based on the consumer response measure for the zero exposure level and the accessed measurement data.

Claims

1. An system comprising:

one or more processing devices;

one or more storage devices storing instructions that, when executed by the one or more processing devices, causes the one or more processing devices to;

access measurement data associated with a group of users that have been exposed to at least one advertising creative that is part of an advertising campaign, the measurement data reflecting one or more consumer responses and one or more non-zero exposure levels, wherein the non-zero exposure levels correspond to non-zero amounts of exposures to at least one advertising creative that is part of the advertising campaign;

generate a model that relates consumer response measures to one or more exposure levels based on the accessed measurement data;

determine, based on the generated model, a consumer response measure for a zero exposure level, wherein the zero exposure level corresponds to a zero amount of exposures to at least one advertising creative that is part of the advertising campaign; and

determine an advertising effectiveness metric based on the consumer response measure for the zero exposure level and the accessed measurement data.

2. The system of claim 1 wherein each of the one or more non-zero exposure levels corresponds to an individual, non-zero number of exposures.

3. The system of claim 1 wherein, to generate the model, the instructions include instructions that, when executed by the one or more processing devices, causes the one or more processing devices to generate, based one the accessed measurement data, a model that relates consumer response measures to exposure levels while holding other factors constant.

4. The system of claim 3 wherein the other factors include age, gender, income level, or usage.

5. The system of claim 1 wherein the consumer response measures are probabilities of a positive consumer response.

6. The system of claim 1 wherein, to determine the advertising effectiveness metric, the instructions include instructions that, when executed by the one or more processing devices, causes the one or more processing devices to:

determine an estimate of the exposure distribution for the advertising campaign, the exposure distribution including one or more non-zero exposure levels experienced during the campaign;

determine, based on the model, consumer response measures for the non-zero exposure levels in the estimate of the exposure distribution;

determine changes of the determined consumer response measures for the non-zero exposure levels in the estimate of the exposure distribution relative to the consumer response measure for the zero exposure level; and

determine an advertising effectiveness metric based on the changes.

7. The system of claim 6 wherein, to determine the estimate, the instructions include instructions that, when executed by the one or more processing devices, causes the one or more processing devices to determine the non-zero exposure levels reflected by the measurement data.

8. The system of claim 7 wherein, to determine an advertising effectiveness metric based on the changes, the instructions include instructions that, when executed by the one or more processing devices, causes the one or more processing devices to:

determine a proportion of the users in the group at each non-zero exposure level reflected by the measurement data;

weight the changes by the corresponding proportions; and

sum the weighted changes.

9. The system of claim 8 wherein the changes are percent changes and the proportions are the percentages of users in the group at each non-zero exposure level.

10. The system of claim 9 wherein, to determine the estimate, the instructions include instructions that, when executed by the one or more processing devices, causes the one or more processing devices to determine one or more non-zero exposure levels experienced by users of a panel.

11. The system of claim 10 wherein, to determine an advertising effectiveness metric based on the changes, the instructions include instructions that, when executed by the one or more processing devices, causes the one or more processing devices to:

determine a proportion of the users in the panel at each non-zero exposure level experienced by the users of the panel;

weight the changes by the corresponding proportions; and

sum the weight changes

12. The system of claim 1 wherein, to determine the advertising effectiveness metric, the instructions include instructions that, when executed by the one or more processing devices, causes the one or more processing devices to:

determine a non-zero exposure level that corresponds to an average number of exposures for the group;

determine a consumer response measure for the non-zero exposure level that corresponds to an average number of exposures for the group; and

determine a change of the consumer response measure for the non-zero exposure level that corresponds to an average number of exposures for the group relative to the consumer response measure for the zero exposure level.

13. The system of claim 12 wherein the change is a percent change.

14. The system of claim 1 wherein the advertising effectiveness measure indicates an effectiveness with respect to one or more attitudinal or behavioral responses.

15. The system of claim 14 wherein the attitudinal responses include one or more of brand favorability, intent to purchase, brand recommendation, unaided awareness, or recall

16. The system of claim 14 wherein the behavioral responses include one or more of website visitation, brand, product, or service searching, or purchase of a product or service.

17. An method comprising:

accessing measurement data associated with a group of users that have been exposed to at least one advertising creative that is part of an advertising campaign, the measurement data reflecting one or more consumer responses and one or more non-zero exposure levels, wherein the non-zero exposure levels correspond to non-zero amounts of exposures to at least one advertising creative that is part of the advertising campaign;

generating a model that relates consumer response measures to one or more exposure levels based on the accessed measurement data;

determining, based on the generated model, a consumer response measure for a zero exposure level, wherein the zero exposure level corresponds to a zero amount of exposures to at least one advertising creative that is part of the advertising campaign; and

determining an advertising effectiveness metric based on the consumer response measure for the zero exposure level and the accessed measurement data.

18. The method of claim 17 wherein determining includes:

determining an estimate of the exposure distribution for the advertising campaign, the exposure distribution including one or more non-zero exposure levels experienced during the campaign;

determining, based on the model, consumer response measures for the non-zero exposure levels in the estimate of the exposure distribution;

determining changes of the determined consumer response measures for the non-zero exposure levels in the estimate of the exposure distribution relative to the consumer response measure for the zero exposure level; and

determining an advertising effectiveness metric based on the changes.

19. The method of claim 18 wherein determining the estimate comprises determining the non-zero exposure levels reflected by the measurement data.

20. The method of claim 19 wherein determining an advertising effectiveness metric based on the changes comprises:

determining a proportion of the users in the group at each non-zero exposure level reflected by the measurement data;

weighting the changes by the corresponding proportions; and

summing the weighted changes.

21. The method of claim 17 wherein determining the advertising effectiveness metric includes:

determining a non-zero exposure level that corresponds to an average number of exposures for the group;

determining a consumer response measure for the non-zero exposure level that corresponds to an average number of exposures for the group; and

determining a change of the consumer response measure for the non-zero exposure level that corresponds to an average number of exposures for the group relative to the consumer response measure for the zero exposure level.

22. A system comprising:

one or more processing devices;

one or more storage devices storing instructions that, when executed by the one or more processing devices, causes the one or more processing devices to;

access measurement data associated with a group of users that have been exposed to at least one advertising creative that is part of an advertising campaign, the measurement data reflecting, for each one of multiple non-zero exposure levels, an amount of the users from the group corresponding to a positive consumer response, wherein each non-zero exposure level corresponds to a non-zero amount of exposures to at least one advertising creative that is part of the advertising campaign;

generate a model that relates probabilities of a positive consumer response to exposure levels based on the accessed measurement data;

determine, based on the generated model, a probability of a positive consumer response for a zero exposure level, wherein the zero exposure level corresponds to a zero amount of exposures to at least one advertising creative that is part of the advertising campaign; and

determine an advertising effectiveness metric based on the probability of a positive consumer response for the zero exposure level and the accessed measurement data.

23. A method comprising:

accessing measurement data associated with a group of users that have been exposed to at least one advertising creative that is part of an advertising campaign, the measurement data reflecting, for each one of multiple non-zero exposure levels, an amount of the users from the group corresponding to a positive consumer response, wherein each non-zero exposure level corresponds to a non-zero amount of exposures to at least one advertising creative that is part of the advertising campaign;

generating a model that relates probabilities of a positive consumer response to exposure levels based on the accessed measurement data;

determining, based on the generated model, a probability of a positive consumer response for a zero exposure level, wherein the zero exposure level corresponds to a zero amount of exposures to at least one advertising creative that is part of the advertising campaign; and

determining an advertising effectiveness metric based on the probability of a positive consumer response for the zero exposure level and the accessed measurement data.