CLASSIFICATION OF GEOGRAPHIC PERFORMANCE DATA
A system for classification, including: (a) at least one storage apparatus configured to store information pertaining to a set of ad entity performance data associated with different geographic locations; and (b) at least one processor configured to: define a classification scheme for classification of the performance data into classes based on at least the geographic location identifier in a defining process which includes assigning a score to the geographic location identifier, based on a plurality of quantities of successful occurrences of performance data, each of the quantities is a quantity of successful occurrences having a corresponding geographic location identifier; obtain a respective subset of the performance data; determine, with respect to each class of the plurality of classes, an outcome estimation; compute, for an analyzed performance data, a performance assessment.
1 . A system for classification, the system comprising:
(a) at least one storage apparatus configured to store information pertaining to a set of ad entity performance data associated with different geographic locations, the information being indicative of:
a quantity of occurrences, larger than one, of the performance data in a sample,
a quantity of successful occurrences of the performance data in the sample, and
at least one geographic location identifier of the performance data; and
(b) at least one processor configured to:
define a classification scheme for classification of the performance data into classes based on at least the geographic location identifier in a defining process which includes assigning a score to the geographic location identifier, based on a plurality of quantities of successful occurrences of performance data, each of the quantities is a quantity of successful occurrences having a corresponding geographic location identifier,
obtain a respective subset of the performance data for each out of a plurality of the classes, by applying the classification scheme to geographic location identifiers of a plurality of performance data of the set,
determine, with respect to each class of the plurality of classes, an outcome estimation based on quantities of successful occurrences of performance data of the respective subset of performance data of said class, and
compute, for an analyzed performance data, a performance assessment which is based on an outcome estimation of a class out of the classes that is a result of application of the classification scheme to geographic location identifiers of the analyzed performance data, thereby enabling a selective application of an industrial process, wherein the selective application is responsive to the performance assessment.
2 . The system according to claim 1 , wherein each occurrence is partial performance data associated with one of said different geographic locations, and each successful occurrence is complete performance data associated with one of said different geographic locations.
3 . The system according to claim 1 , wherein the selective application comprises determining a geographic bid modifier for an ad entity
4 . The system according to claim 3 , wherein the determining of the geographic bid modifier for the ad entity comprises computing a ratio between:
a value per click for the ad entity; and
an average value per click across ad entities of all the different geographic locations.
5 . The system according to claim 4 , wherein the value per click and the average value per click are at least partially based on a geographic parameter selected from the group consisting of: a demographic parameter, a business parameter associated with an advertiser, a geographic reach of an advertising platform, weather data and news data.
6 . The system according to claim 3 , wherein the determining of the geographic bid modifier for the ad entity comprises computing a ratio between:
a value per impression for the ad entity; and
an average value per impression across ad entities of all the different geographic locations.
7 . The system according to claim 6 , wherein the value per impression and the average value per impression are at least partially based on a geographic parameter selected from the group consisting of: a demographic parameter, a business parameter associated with an advertiser, a geographic reach of an advertising platform, weather data and news data.
8 . The system according to claim 1 , wherein the ad entity is selected from the group consisting of: an individual ad, a set of ads, a campaign and a set of campaigns.
9 . The system according to claim 1 , wherein the performance data comprises at least one performance metric selected from the group consisting of: impressions, clicks, click-through rate (CTR), conversions, return on investment (ROI), revenue per click, cost per impression, cost per click, revenue per impression, reach and frequency.
10 . The system according to claim 3 , wherein said at least one processor is further configured to transmit a command to an advertising platform, the command being based on the geographic bid modifier for the ad entity.
11 . A computerized method for classification, the method comprising:
(a) storing, in at least one storage apparatus, information pertaining to a set of ad entity performance data associated with different geographic locations, the information being indicative of:
a quantity of occurrences, larger than one, of the performance data in a sample,
a quantity of successful occurrences of the performance in the sample, and
at least one geographic location identifier of the performance data; and
(b) using at least one processor to:
define a classification scheme for classification of the performance data into classes based on at least the geographic location identifier in a defining process which includes assigning a score to the geographic location identifier, based on a plurality of quantities of successful occurrences of performance data, each of the quantities is a quantity of successful occurrences having a corresponding geographic location identifier,
obtain a respective subset of the performance data for each out of a plurality of the classes, by applying the classification scheme to geographic location identifiers of a plurality of performance data of the set,
determine, with respect to each class of the plurality of classes, an outcome estimation based on quantities of successful occurrences of performance data of the respective subset of performance data of said class, and
compute, for an analyzed performance data, a performance assessment which is based on an outcome estimation of a class out of the classes that is a result of application of the classification scheme to geographic location identifiers of the analyzed performance data, thereby enabling a selective application of an industrial process, wherein the selective application is responsive to the performance assessment.
12 . The method according to claim 11 , wherein each occurrence is partial performance data associated with one of said different geographic locations, and each successful occurrence is complete performance data associated with one of said different geographic locations.
13 . The method according to claim 10 , wherein the selective application comprises determining a geographic bid modifier for an ad entity.
14 . The method according to claim 13 , wherein the determining of the geographic bid modifier for the ad entity comprises computing a ratio between:
a value per click for the ad entity; and
an average value per click across ad entities of all the different geographic locations.
15 . The method according to claim 14 , wherein the value per click and the average value per click are at least partially based on a geographic parameter selected from the group consisting of: a demographic parameter, a business parameter associated with an advertiser, a geographic reach of an advertising platform, weather data and news data.
16 . The method according to claim 13 , wherein the determining of the geographic bid modifier for the ad entity comprises computing a ratio between:
a value per impression for the ad entity; and
an average value per impression across ad entities of all the different geographic locations.
17 . The system according to claim 16 , wherein the value per impression and the average value per impression are at least partially based on a geographic parameter selected from the group consisting of: a demographic parameter, a business parameter associated with an advertiser, a geographic reach of an advertising platform, weather data and news data.
18 . The method according to claim 11 , wherein the ad entity is selected from the group consisting of: an individual ad, a set of ads, a campaign and a set of campaigns.
19 . The method according to claim 11 , wherein the performance data comprises at least one performance metric selected from the group consisting of: impressions, clicks, click-through rate (CTR), conversions, return on investment (ROI), revenue per click, cost per impression, cost per click, revenue per impression, reach and frequency.
20 . The method according to claim 13 , wherein said at least one processor is further configured to transmit a command to an advertising platform, the command being based on the geographic bid modifier for the ad entity.
21 . A program storage device readable by machine, tangibly embodying a program of instructions executable by the machine to perform a method for classification, comprising the steps of:
(a) storing, in at least one storage apparatus, information pertaining to a set of ad entity performance data associated with different geographic locations, the information being indicative of:
a quantity of occurrences, larger than one, of the performance data in a sample,
a quantity of successful occurrences of the performance in the sample, and
at least one geographic location identifier of the performance data; and
(b) using at least one processor to:
define a classification scheme for classification of the performance data into classes based on at least the geographic location identifier in a defining process which includes assigning a score to the geographic location identifier, based on a plurality of quantities of successful occurrences of performance data, each of the quantities is a quantity of successful occurrences having a corresponding geographic location identifier,
obtain a respective subset of the performance data for each out of a plurality of the classes, by applying the classification scheme to geographic location identifiers of a plurality of performance data of the set,
determine, with respect to each class of the plurality of classes, an outcome estimation based on quantities of successful occurrences of performance data of the respective subset of performance data of said class, and
compute, for an analyzed performance data, a performance assessment which is based on an outcome estimation of a class out of the classes that is a result of application of the classification scheme to geographic location identifiers of the analyzed performance data, thereby enabling a selective application of an industrial process, wherein the selective application is responsive to the performance assessment.
22 . The program storage device according to claim 21 , wherein each occurrence is partial performance data associated with one of said different geographic locations, and each successful occurrence is complete performance data associated with one of said different geographic locations.
23 . The program storage device according to claim 21 , wherein the selective application comprises determining a geographic bid modifier for an ad entity.
24 . The program storage device according to claim 23 , wherein the determining of the geographic bid modifier for the ad entity comprises computing a ratio between:
a value per click for the ad entity; and
an average value per click across ad entities of all the different geographic locations.
25 . The program storage device according to claim 23 , wherein the value per click and the average value per click are at least partially based on a geographic parameter selected from the group consisting of: a demographic parameter, a business parameter associated with an advertiser, a geographic reach of an advertising platform, weather data and news data.
26 . The program storage device according to claim 23 , wherein the determining of the geographic bid modifier for the ad entity comprises computing a ratio between:
a value per impression for the ad entity; and
an average value per impression across ad entities of all the different geographic locations.
27 . The program storage device according to claim 26 , wherein the value per impression and the average value per impression are at least partially based on a geographic parameter selected from the group consisting of: a demographic parameter, a business parameter associated with an advertiser, a geographic reach of an advertising platform, weather data and news data.
28 . The method according to claim 21 , wherein the ad entity is selected from the group consisting of: an individual ad, a set of ads, a campaign and a set of campaigns.
29 . The program storage device according to claim 21 , wherein the performance data comprises at least one performance metric selected from the group consisting of: impressions, clicks, click-through rate (CTR), conversions, return on investment (ROI), revenue per click, cost per impression, cost per click, revenue per impression, reach and frequency.
30 . The program storage device according to claim 23 , wherein said at least one processor is further configured to transmit a command to an advertising platform, the command being based on the geographic bid modifier for the ad entity.