Affinity profile system and method
A computer-implemented method of targeting users based on content consumption comprises: for each of a plurality of users, monitoring user activity including identifying content selected for viewing by the users; obtaining metadata concerning the selected items of content, the metadata representing at least some properties of the selected items of content; generating or updating a user record for each user, the user record comprising or representing the user activity and/or the associated content metadata; and identifying users that have below a threshold level of user activity.
1. A computer-implemented method of targeting users based on content consumption comprising:
for each of a plurality of users, monitoring user activity including identifying content selected for viewing by the users;
obtaining metadata concerning the selected items of content,
the metadata representing at least some properties of the selected items of content;
generating or updating a user record for each user,
the user record comprising or representing at least one of the user activity or the associated content metadata,
wherein for at least some of the users, the user record does not include any data representing socio-economic or demographic status;
for each user, generating an affinity profile based on the user record for the user,
wherein the affinity profile comprises at least one selected affinity category or affinity category score;
categorizing the users into one or more of a plurality of affinity segments based on their affinity profile,
wherein each affinity segment corresponds to an area of interest; and
for at least one of the affinity segments, classifying each of a plurality of the users that are categorized into that affinity segment into one of a plurality of classifications based on the amount of content each of the plurality of the users viewed over a period of time,
wherein the period of time comprises at least one day, and
wherein the plurality of classifications comprises at least a lighter viewer classification and a heavier viewer classification.
2. The method of claim 1 , comprising for each user processing the user record of the user to generate an affinity profile for the user based on the user record, the affinity profile comprising at least one selected affinity category or affinity category score.
3. The method of claim 2 , comprising selecting items of content that are expected to be attractive to at least some of the users identified as having below a threshold level of user activity, wherein the selecting of items of content is based on the affinity profiles for the users.
4. The method of claim 2 , comprising selecting first 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 of the users for the advertisements;
determining at least some of the users that are identified as having below a threshold level of user activity and thus who may be expected not to view the first items of content; and
selecting second items of content that are expected to be attractive to at least some of the users identified as having below the threshold level of user activity, wherein the selecting of items of content is based on the affinity profiles for the users.
5. The method of claim 2 , comprising categorizing each user into one or more of a plurality of user segments based on their affinity profile.
6. The method of claim 5 , comprising using the user segments to selecting first items of content for which to include advertisements as part of an advertising campaign for a product or service thereby to target a selected user segment for the advertisements;
determining at least some of the users of the user segment that are identified as having below a threshold level of user activity and thus who may be expected not to view the first items of content; and
selecting second items of content that are expected to be attractive to at least some of the users of the selected user segment identified as having below the threshold level of user activity, wherein the selecting of items of content is based on the affinity profiles for the users.
7. The method of claim 5 , wherein at least some of the user segments represent at least one of: an area of interest, a combination of areas of interest, a demographic category, an amount of viewing, an amount of other consumption of content, or a time period when consumption of content is most likely.
8. The method of claim 5 , wherein the categorizing each user into one or more of the plurality of user segments is based on the user records of the users.
9. The method of claim 2 , wherein the user interface is operable by a user to select one or more items of content of content types other than television content,
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
the other content types comprises at least one of computer games, books, music, spoken word content, other audio content, newspapers, or magazines.
10. The method of claim 2 , wherein the generating of the affinity profiles is independent of, or is performed without taking into account, data representing socio-economic or demographic status of the users.
11. The method of claim 2 , 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;
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.
12. The method of claim 2 , wherein at least one of:
the at least one selected affinity category comprises at least 100 affinity categories or sub-categories;
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.
13. The method of claim 2 , 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.
14. The method of claim 2 , wherein the affinity profile for each user comprises a set of scores, each score being for a respective one of the affinity categories.
15. The method of claim 2 , wherein each user is a user account, a plurality of individuals may have access to the user account and/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 selection of content by the plurality of individuals and/or using the plurality of user devices.
16. The method of claim 2 , further comprising selecting additional television content or other content to push to the user based on the determined affinity profile for the user.
17. The method of claim 2 , further comprising outputting the affinity profiles for 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.
18. 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.
19. A non-transitory computer-readable medium that comprises computer-readable instructions that are executable to perform a method according to claim 1 .
20. A system comprising processing circuitry configured to:
for each of a plurality of users, monitor user activity including identifying content selected for viewing by the users;
obtain metadata concerning the selected items of content,
the metadata representing at least some properties of the selected items of content;
generate or update a user record for the user,
the user record comprising or representing at least one of the user activity and/or the associated content metadata,
wherein for at least some of the users, the user record does not include any data representing socio-economic or demographic status;
for each user, generate an affinity profile based on the user record for the user,
wherein the affinity profile comprises at least one selected affinity category or affinity category score;
categorize the users into one or more of a plurality of affinity segments based on their affinity profile,
wherein each affinity segment corresponds to an area of interest; and
for at least one of the affinity segments, classify each of a plurality of the users that are categorized into that affinity segment into one of a plurality of classifications based on the amount of content each of the plurality of the users viewed over a period of time,
wherein the period of time comprises at least one day, and
wherein the plurality of classifications comprises at least a lighter viewer classification and a heavier viewer classification.