METHOD AND SYSTEM FOR FORECASTING PERFORMANCE OF AUDIENCE CLUSTERS
The present teaching relates to method, system, and medium for predicting performance of an audience cluster. First information related to a plurality of users in the audience cluster is received. A plurality of advertisements are received that are previously placed at an advertisement exposure opportunity and presented to the plurality of users, wherein each of the plurality of advertisements placed at the advertisement exposure opportunity is associated with first criteria. Second information related to events involving the plurality of users with respect to the plurality of advertisements is obtained and performance of the audience cluster associated with the advertisement exposure opportunity is predicted based on the obtained first information and second information in accordance with at least one prediction model and with respect to the first criteria. The predicted performance of the audience cluster is used for ordering a plurality of audience clusters associated with the advertisement exposure opportunity.
1 . A method implemented on a computer having at least one processor, a storage, and a communication platform for predicting performance of an audience cluster, the method comprising:
receiving first information related to a plurality of users in the audience cluster;
receiving a plurality of advertisements previously placed at an advertisement exposure opportunity and presented to the plurality of users, wherein each of the plurality of advertisements placed at the advertisement exposure opportunity is associated with first criteria;
obtaining second information related to events involving the plurality of users with respect to the plurality of advertisements;
predicting, performance of the audience cluster associated with the advertisement exposure opportunity based on the obtained first information and second information in accordance with at least one prediction model and with respect to the first criteria; and
providing the predicted performance of the audience cluster to order a plurality of audience clusters associated with the advertisement exposure opportunity.
2 . The method of claim 1 , wherein the first information includes for each of the plurality of users, at least a gender of the user, a geographical location of the user, and an operating system utilized by the user.
3 . The method of claim 1 , wherein the second information corresponds to interaction information of the plurality of users with respect to the plurality of advertisements.
4 . The method of claim 3 , wherein the interaction information includes a time at which an advertisement was consumed by a user.
5 . The method of claim 1 , wherein the second information is obtained across different platforms and media types.
6 . The method of claim 1 , further comprising:
updating the predicted performance of the audience cluster in response to a condition being satisfied.
7 . The method of claim 6 , wherein the condition corresponds to one of obtaining a predetermined amount of second information, and an occurrence of a scheduled update.
8 . The method of claim 1 , wherein the performance of the audience cluster is predicted with respect to the first criteria, which includes one or more parameters related to at least a size of the audience cluster, a viewability of the audience cluster, a CTR of the audience cluster, and a make-up of the audience cluster.
9 . A non-transitory machine-readable medium having information recorded thereon, wherein the information, when read by the machine, causes the machine to perform the following:
receiving first information related to a plurality of users in the audience cluster;
receiving a plurality of advertisements previously placed at an advertisement exposure opportunity and presented to the plurality of users, wherein each of the plurality of advertisements placed at the advertisement exposure opportunity is associated with first criteria;
obtaining second information related to events involving the plurality of users with respect to the plurality of advertisements;
predicting, performance of the audience cluster associated with the advertisement exposure opportunity based on the obtained first information and second information in accordance with at least one prediction model and with respect to the first criteria; and
providing the predicted performance of the audience cluster to order a plurality of audience clusters associated with the advertisement exposure opportunity.
10 . The non-transitory machine-readable medium of claim 9 , wherein the first information includes for each of the plurality of users, at least a gender of the user, a geographical location of the user, and an operating system utilized by the user.
11 . The non-transitory machine-readable medium of claim 9 , wherein the second information corresponds to interaction information of the plurality of users with respect to the plurality of advertisements.
12 . The non-transitory machine-readable medium of claim 11 , wherein the interaction information includes a time at which an advertisement was consumed by a user.
13 . The non-transitory machine-readable medium of claim 9 , wherein the second information is obtained across different platforms and media types.
14 . The non-transitory machine-readable medium of claim 9 , wherein the machine further performs the step of:
updating the predicted performance of the audience cluster in response to a condition being satisfied.
15 . The non-transitory machine-readable medium of claim 14 , wherein the condition corresponds to one of obtaining a predetermined amount of second information, and an occurrence of a scheduled update.
16 . The non-transitory machine-readable medium of claim 9 , wherein the performance of the audience cluster is predicted with respect to the first criteria, which includes one or more parameters related to at least a size of the audience cluster, a viewability of the audience cluster, a CTR of the audience cluster, and a make-up of the audience cluster.
17 . A system for predicting performance of an audience cluster, the system comprising:
a receiving unit configured to
receive first information related to a plurality of users in the audience cluster,
receive a plurality of advertisements previously placed at an advertisement exposure opportunity and presented to the plurality of users, wherein each of the plurality of advertisements placed at the advertisement exposure opportunity is associated with first criteria, and
obtain second information related to events involving the plurality of users with respect to the plurality of advertisements; and
a predicting unit configured to
predict, performance of the audience cluster associated with the advertisement exposure opportunity based on the obtained first information and second information in accordance with at least one prediction model and with respect to the first criteria, and
provide the predicted performance of the audience cluster to order a plurality of audience clusters associated with the advertisement exposure opportunity.
18 . The system of claim 17 , wherein the performance of the audience cluster is predicted with respect to the first criteria, which includes one or more parameters related to at least a size of the audience cluster, a viewability of the audience cluster, a CTR of the audience cluster, and a make-up of the audience cluster.