METHOD AND SYSTEM FOR FORECASTING PERFORMANCE OF PERSISTENT USER ACCOUNTS
The present teaching relates to method, system, and medium for obtaining consumption data. A first request is received to retrieve a plurality of data sets, each of which is related to one of a plurality of accounts in an audience cluster, each account is represented by a persistent identifier that links multiple identifiers associated with one or more devices, or platforms on which content is consumed in at least one media type. Information related to content consumption on a device/platform associated with each of the linked multiple identifiers of the account is retrieved, and a data set of the account is provided based on information retrieved with respect to each of the linked multiple identifiers. The data set is presented in one representation upon a request for information about the account and retrieved data sets are provided in response to the first request, for forecasting performance of audience clusters.
1 . A method implemented on a computer having at least one processor, a storage, and a communication platform for obtaining consumption data, the method comprising:
receiving a first request to retrieve a plurality of data sets, each of which is related to one of a plurality of accounts in an audience cluster, wherein each of the plurality of accounts is represented by a persistent identifier that links multiple identifiers associated with one or more devices or one or more platforms on which content is consumed in at least one media type;
for each of the plurality of accounts,
retrieving information related to content consumption on a device/platform associated with each of the linked multiple identifiers of the account,
providing a data set of the account based on information retrieved with respect to each of the linked multiple identifiers, and
presenting the data set in one representation upon a request for information about the account; and
providing the retrieved plurality of data sets in response to the first request, wherein the plurality of data sets are to be used to forecast performance of the audience cluster.
2 . The method of claim 1 , wherein the first request is received from an advertiser and/or a publisher.
3 . The method of claim 1 , wherein each of the plurality of accounts in the audience cluster is associated with a granularity level, the granularity level being determined based on a number of users associated with the account.
4 . The method of claim 3 , wherein the granularity level is one of an individual level, a household level, a social-group level, and an organization level.
5 . The method of claim 4 , wherein each of the household level, the social-group level, and the organization level include a plurality of users associated with the account, and a plurality of devices associated with each of the plurality of users.
6 . A system for obtaining consumption data, the system comprising:
a single source panel unit configured to
receive a first request to retrieve a plurality of data sets, each of which is related to one of a plurality of accounts in an audience cluster, wherein each of the plurality of accounts is represented by a persistent identifier that links multiple identifiers associated with one or more devices or one or more platforms on which content is consumed in at least one media type;
for each of the plurality of accounts,
retrieve information related to content consumption on a device/platform associated with each of the linked multiple identifiers of the account,
provide a data set of the account based on information retrieved with respect to each of the linked multiple identifiers, and
present the data set in one representation upon a request for information about the account; and
provide the retrieved plurality of data sets in response to the first request, wherein the plurality of data sets are to be used to forecast performance of the audience cluster.
7 . The system of claim 6 , wherein the first request is received from an advertiser and/or a publisher.
8 . The system of claim 6 , wherein each of the plurality of accounts in the audience cluster is associated with a granularity level, the granularity level being determined based on a number of users associated with the account.
9 . The system of claim 8 , wherein the granularity level is one of an individual level, a household level, a social-group level, and an organization level.
10 . The system of claim 9 , wherein each of the household level, the social-group level, and the organization level include a plurality of users associated with the account, and a plurality of devices associated with each of the plurality of users.
11 . 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 a first request to retrieve a plurality of data sets, each of which is related to one of a plurality of accounts in an audience cluster, wherein each of the plurality of accounts is represented by a persistent identifier that links multiple identifiers associated with one or more devices or one or more platforms on which content is consumed in at least one media type;
for each of the plurality of accounts,
retrieving information related to content consumption on a device/platform associated with each of the linked multiple identifiers of the account,
providing a data set of the account based on information retrieved with respect to each of the linked multiple identifiers, and
presenting the data set in one representation upon a request for information about the account; and
providing the retrieved plurality of data sets in response to the first request, wherein the plurality of data sets are to be used to forecast performance of the audience cluster.
12 . The non-transitory machine-readable medium of claim 11 , wherein the first request is received from an advertiser and/or a publisher.
13 . The non-transitory machine-readable medium of claim 11 , wherein each of the plurality of accounts in the audience cluster is associated with a granularity level, the granularity level being determined based on a number of users associated with the account.
14 . The non-transitory machine-readable medium of claim 13 , wherein the granularity level is one of an individual level, a household level, a social-group level, and an organization level.
15 . The non-transitory machine-readable medium of claim 14 , wherein each of the household level, the social-group level, and the organization level include a plurality of users associated with the account, and a plurality of devices associated with each of the plurality of users.