METHODS AND APPARATUS TO EVALUATE ADVERTISING CAMPAIGNS
Methods, apparatus, systems and articles of manufacture are disclosed to evaluate advertising campaigns. An example method disclosed herein includes calculating a first coordinate value based on a first effectiveness value and a first audience qualification score associated with a first advertising campaign, calculating a second coordinate value based on a second effectiveness value and a second audience qualification score associated with a second advertising campaign, identifying an apex score indicative of a maximum potential effectiveness value and a maximum potential audience qualification score, calculating a first improvement value based on a distance between the first coordinate value and the apex score, and calculating a second improvement value based on a distance between the second coordinate value and the apex score, and determining whether to adjust the first advertising campaign or the second advertising campaign based on a comparison between the first improvement value and the second improvement value.
1 . A method to identify an improvement opportunity for first and second advertising campaigns, comprising:
calculating a first coordinate value based on a first effectiveness value and a first audience qualification score associated with the first advertising campaign;
calculating a second coordinate value based on a second effectiveness value and a second audience qualification score associated with the second advertising campaign;
identifying an apex score indicative of a maximum potential effectiveness value and a maximum potential audience qualification score;
calculating a first improvement value based on a distance between the first coordinate value and the apex score, and calculating a second improvement value based on a distance between the second coordinate value and the apex score; and
determining whether to adjust the first advertising campaign or the second advertising campaign based on a comparison between the first improvement value and the second improvement value.
2 . A method as defined in claim 1 , further comprising calculating a variance value between the first and the second improvement values.
3 . A method as defined in claim 2 , further comprising recalculating the first and the second improvement values based on an area metric when the variance value is below a threshold.
4 . A method as defined in claim 1 , wherein the first and the second improvement values are calculated based on a Euclidian distance from the apex score.
5 . A method as defined in claim 1 , further comprising ranking the first advertising campaign and the second advertising campaign based on the first and the second improvement values.
6 . A method as defined in claim 5 , further comprising identifying a driver type associated with a highest ranking advertising campaign improvement value.
7 . A method as defined in claim 1 , further comprising identifying a first predisposition score associated with the first advertising campaign and a second predisposition score associated with the second advertising campaign.
8 . A method as defined in claim 7 , further comprising calculating a maximum potential effectiveness value for the first advertising campaign and the second advertising campaign based on the first and the second predisposition scores, respectively.
9 . A method as defined in claim 7 , wherein the first predisposition score is indicative of a portion of an audience that agrees with the first advertising campaign prior to exposure thereto.
10 . A method as defined in claim 1 , wherein the first audience qualification score is based on a percentage of total advertising impressions delivered to a target audience associated with the first advertising campaign.
11 . An apparatus to identify an improvement opportunity for first and second advertising campaigns, comprising:
a distance calculator to calculate a first coordinate value based on a first effectiveness value and a first audience qualification score associated with the first advertising campaign, and to calculate a second coordinate value based on a second effectiveness value and a second audience qualification score associated with the second advertising campaign;
an apex generator to identify an apex score indicative of a maximum potential effectiveness value and a maximum potential audience qualification score;
a persuasion calculator to calculate a first improvement value based on a distance between the first coordinate value and the apex score, and calculating a second improvement value based on a distance between the second coordinate value and the apex score; and
a campaign manager to determine whether to adjust the first advertising campaign or the second advertising campaign based on a comparison between the first improvement value and the second improvement value.
12 . An apparatus as defined in claim 11 , further comprising a variance calculator to calculate a variance value between the first and the second improvement values.
13 . An apparatus as defined in claim 12 , further comprising an area A-score calculator to recalculate the first and the second improvement values based on an area metric when the variance value is below a threshold.
14 . An apparatus as defined in claim 11 , wherein the distance calculator is to calculate the first and the second improvement values based on a Euclidian distance from the apex score.
15 . An apparatus as defined in claim 11 , further comprising a report manager to rank the first advertising campaign and the second advertising campaign based on the first and the second improvement values.
16 . An apparatus as defined in claim 15 , further comprising a campaign driver manager to identify a driver type associated with a highest ranking advertising campaign improvement value.
17 . An apparatus as defined in claim 11 , wherein the persuasion calculator is to identify a first predisposition score associated with the first advertising campaign and a second predisposition score associated with the second advertising campaign.
18 . An apparatus as defined in claim 17 , wherein the persuasion calculator is to calculate a maximum potential effectiveness value for the first advertising campaign and the second advertising campaign based on the first and the second predisposition scores, respectively.
19 . An apparatus as defined in claim 17 , wherein the first predisposition score is indicative of a portion of an audience that agrees with the first advertising campaign prior to exposure thereto.
20 . An apparatus as defined in claim 11 , wherein the first audience qualification score is based on a percentage of total advertising impressions delivered to a target audience associated with the first advertising campaign.
21 . A tangible machine readable storage medium comprising instructions that when executed, cause a machine to, at least:
calculate a first coordinate value based on a first effectiveness value and a first audience qualification score associated with the first advertising campaign;
calculate a second coordinate value based on a second effectiveness value and a second audience qualification score associated with the second advertising campaign;
identify an apex score indicative of a maximum potential effectiveness value and a maximum potential audience qualification score;
calculate a first improvement value based on a distance between the first coordinate value and the apex score, and calculate a second improvement value based on a distance between the second coordinate value and the apex score; and
determine whether to adjust the first advertising campaign or the second advertising campaign based on a comparison between the first improvement value and the second improvement value.
22 . A storage medium as defined in claim 21 , wherein the instructions, when executed, further cause the machine to calculate a variance value between the first and the second improvement values.
23 . A storage medium as defined in claim 22 , wherein the instructions, when executed, further cause the machine to recalculate the first and the second improvement values based on an area metric when the variance value is below a threshold.
24 . A storage medium as defined in claim 21 , wherein the instructions, when executed, further cause the machine to calculate the first and the second improvement values based on a Euclidian distance from the apex score.
25 . A storage medium as defined in claim 21 , wherein the instructions, when executed, further cause the machine to rank the first advertising campaign and the second advertising campaign based on the first and the second improvement values.
26 . A storage medium as defined in claim 25 , wherein the instructions, when executed, further cause the machine to identify a driver type associated with a highest ranking advertising campaign improvement value.
27 . A storage medium as defined in claim 21 , wherein the instructions, when executed, further cause the machine to identify a first predisposition score associated with the first advertising campaign and a second predisposition score associated with the second advertising campaign.
28 . A storage medium as defined in claim 27 , wherein the instructions, when executed, further cause the machine to calculate a maximum potential effectiveness value for the first advertising campaign and the second advertising campaign based on the first and the second predisposition scores, respectively.