Affinity profile system and method
A computer-implemented method of using affinity profiles to determine at least one audience category that is expected to consume a selected item of content, the method comprises: obtaining affinity profiles for a plurality of users of a content distribution system, wherein each affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area; determine an audience that is expected to consume the selected item of content based on the affinity profiles of the users.
1. A computer-implemented method of using affinity profiles to determine at least one audience category that is expected to consume a selected item of content, the method comprising:
obtaining affinity profiles for a plurality of users of a content distribution system,
wherein each affinity profile comprises at least one selected affinity category or affinity category score,
wherein the affinity categories are selected from a stored set of affinity categories, and
wherein each of the affinity categories represent a user's affinity for a respective subject area;
monitoring consumption of the selected item of content to determine which of the users consumed the selected item of content; and
determining an audience that is expected to consume the selected item of content based on the affinity profiles of the users, by:
defining a bespoke user segment comprising the users that were determined to have consumed the selected item of content; and
categorizing each user into one or more of a plurality of user segments based on their affinity profile; and
determining the audience that is expected to consume the selected item of content based on the user segments to which the users in the bespoke user segment, who consumed the selected item of content, belong.
2. The method of claim 1 , further comprising determining expected audiences for a plurality of items of content for which to include advertisements as part of an advertising campaign for a product or service thereby to target at least a sub-set of a desired target audience for the advertisements.
3. The method of claim 1 , further comprising:
for each of a plurality of user devices, monitoring user activity including identifying content selected for viewing by the users of the user devices;
obtaining metadata concerning the selected items of content, the metadata representing at least some properties of the selected items of content;
generating or updating user records for the users, the user records comprising or representing at least one of the user activity or the associated content metadata;
processing the user records to generate the affinity profiles for the users based on the user records.
4. The method of claim 3 ,
wherein the item of content is provided to user devices of the users using a content distribution system,
wherein each user device displays an electronic programme guide (EPG) or other user interface that is operable by a user to select one or more items of television or other content,
wherein, in response to the selections, the distribution system distributes the selected items of television content or other content to the user devices for viewing by the users during content viewing sessions,
wherein the user interface is operable by a user to select one or more items of content of content types other than television content,
wherein the obtaining of metadata, the generating or updating of the user record, and the processing of the user record to generate the affinity profile are performed using the content metadata obtained for both selected items of television content and selected items of content of the other content types, and
wherein the other content types comprise at least one of computer games, books, music, spoken word content, other audio content, newspapers, or magazines.
5. The method of claim 3 , wherein the metadata concerning the selected items of content is obtained from a stored ontology that includes at least 10,000 features that can be used as meta data to represent items of content.
6. The method of claim 3 , wherein the processing of the user record to generate an affinity profile comprises applying a mapping process to map between the metadata in the user record and the affinity categories, the mapping process including applying weightings or confidence scores for mappings between metadata in the user record and items in the affinity categories.
7. The method of claim 1 , wherein the item of content is provided to user devices of the users using a content distribution system, wherein each user device displays an electronic programme guide (EPG) or other user interface that is operable by a user to select one or more items of television or other content, and in response to the selections the distribution system distributes the selected items of television content or other content to the user devices for viewing by the users during content viewing sessions.
8. The method of claim 1 , wherein the determining of the audience for the selected item of content comprises providing at least one of the affinity profiles or user records of the users as inputs to a machine learning model that is trained to output an audience based on at least one of the affinity profiles or user records of the users.
9. The method of claim 1 , wherein the obtaining of the affinity profile is independent of, or is performed without taking into account, data representing socio-economic or demographic status of the users.
10. The method of claim 9 , wherein at least one of a), b) or c):
a) the user record for each user does not include any data representing socio-economic or demographic status of the user;
b) the user record for each user is anonymous; or
c) the obtaining of metadata, the generating or updating of user records, and the processing of the user records to generate affinity profiles are performed by processing circuitry that does not have access to at least one of or all of data representing socio-economic or demographic status of the users or identity of the users.
11. The method of claim 1 , wherein the stored set of affinity categories comprises at least 100 affinity categories or sub-categories.
12. The method of claim 1 , wherein the user record comprises or represent user activity for different time windows during a day or week, and the method comprises generating different affinity profiles for the user for the different time windows.
13. The method of claim 1 , wherein the affinity profile for each user comprises a set of scores, each score being for a respective one of the affinity categories.
14. The method of claim 1 ,
wherein each user is a user account, a plurality of individuals may have access to at least one of the user account or wherein a plurality of user devices may be associated with the user account, and
wherein the affinity profile for the user account is based on at least one of selection of content by the plurality of individuals or using the plurality of user devices.
15. The method according to claim 1 , further comprising selecting additional television content or other content to push to the user based on the determined affinity profile for the user.
16. The method according to claim 1 , further comprising outputting the affinity profiles for at least one of the plurality of users and/or the audience category, via an API or operator interface thereby making the affinity profiles available to a third party external to the content distribution system.
17. A non-transitory computer-readable medium that comprises computer-readable instructions that are executable to perform a method according to claim 1 .
18. A system comprising processing circuitry configured to:
obtain affinity profiles for a plurality of users of a content distribution system,
wherein each affinity profile comprises at least one selected affinity category or affinity category score,
wherein the affinity categories are selected from a stored set of affinity categories, and
wherein each of the affinity categories represent a user's affinity for a respective subject area;
monitor consumption of the selected item of content to determine which of the users consumed the item of content;
determine an audience category that is expected to consume the selected item of content based on the affinity profiles of the users that were determined to have consumed the content, by:
defining a bespoke user segment comprising the users that were determined to have consumed the selected item of content; and
categorizing each user into one or more of a plurality of user segments based on their affinity profile; and
determining the audience that is expected to consume the selected item of content based on the user segments to which the users in the bespoke user segment, who consumed the selected item of content, belong.