Recommending a composite channel

1. A method comprising:

identifying a plurality of component channels of a content platform, wherein each of the plurality of component channels comprises an associated individual subscription price;

generating, by a processing device, a user interest score for each of the plurality of component channels;

defining a composite channel comprising a subset of the component channels, wherein the user interest score for each component channel in the subset of the component channels exceeds a predetermined threshold;

determining a composite channel subscription price that is different than a sum of each individual subscription price for each of the component channels included in the composite channel;

determining a recommendation event for the composite channel; and

upon detecting the recommendation event, providing a recommendation to a user to subscribe to the composite channel.

2. The method of claim 1 , wherein the user interest score indicates an affinity of the user for each of the plurality of component channels.

3. The method of claim 1 , wherein generating the user interest score for each of the plurality of component channels comprises determining a predicted amount of consumption of the user for each of the respective component channels within a period of time.

4. The method of claim 1 , wherein the recommendation event comprises activity of the user in relation to at least one of the component channels included in the composite channel.

5. The method of claim 4 , wherein the at least one of the component channels is a channel to which the user has previously subscribed.

6. The method of claim 1 , wherein the plurality of component channels comprises a first set of channels, a second set of channels and a third set of channels, wherein defining the composite channel comprises:

selecting one channel from the first set of channels;

selecting one channel from the second set of channels; and

selecting one channel from the third set of channels.

7. The method of claim 1 further comprising receiving a request from the user to subscribe to the composite channel.

8. The method of claim 1 , wherein the content platform is internet-based.

9. A system, comprising:

a memory; and

a processing device coupled with the memory, to:

identify a plurality of component channels of a content platform, wherein each of the plurality of component channels comprises an associated individual subscription price;

generate a user interest score for each of the plurality of component channels;

define a composite channel comprising a subset of the component channels, wherein the user interest score for each component channel in the subset of the component channels exceeds a predetermined threshold;

determine a composite channel subscription price that is different than a sum of each individual subscription price for each of the component channels included in the composite channel;

determine a recommendation event for the composite channel; and

upon detecting the recommendation event, provide a recommendation to a user to subscribe to the composite channel.

10. The system of claim 9 , wherein generating the user interest score for each of the plurality of component channels comprises determining a predicted amount of consumption of the user for each of the respective component channels within a period of time.

11. The system of claim 9 , wherein the recommendation event comprises activity of the user in relation to at least one of the component channels included in the composite channel.

12. The system of claim 9 , wherein each of the plurality of component channels comprises an associated individual subscription price.

13. A non-transitory computer readable storage medium, having instructions stored therein, which when executed, cause a processing device to perform operations comprising:

identifying a plurality of component channels of a content platform, wherein each of the plurality of component channels comprises an associated individual subscription price;

generating, by the processing device, a user interest score for each of the plurality of component channels;

defining a composite channel comprising a subset of the component channels, wherein the user interest score for each component channel in the subset of the component channels exceeds a predetermined threshold;

determining a composite channel subscription price that is different than a sum of each individual subscription price for each of the component channels included in the composite channel;

determining a recommendation event for the composite channel; and

upon detecting the recommendation event, providing a recommendation to a user to subscribe to the composite channel.

14. The non-transitory computer readable storage medium of claim 13 , wherein the user interest score indicates an affinity of the user for each of the plurality of component channels.

15. The non-transitory computer readable storage medium of claim 13 , wherein generating the user interest score for each of the plurality of component channels comprises determining a predicted amount of consumption of the user for each of the respective component channels within a period of time.

16. The non-transitory computer readable storage medium of claim 13 , wherein the recommendation event comprises activity of the user in relation to at least one of the component channels included in the composite channel.

17. The non-transitory computer readable storage medium of claim 13 , wherein the plurality of component channels comprises a first set of channels, a second set of channels and a third set of channels, wherein defining the composite channel comprises:

selecting one channel from the first set of channels;

selecting one channel from the second set of channels; and

selecting one channel from the third set of channels.

18. A method comprising:

determining, by a processing device, a recommendation event for recommending a composite channel to a user;

identifying, by the processing device, a plurality of component channels pertaining to the recommendation event, wherein each of the plurality of component channels comprises an associated individual subscription price;

generating, by the processing device, a user interest score for each of the plurality of component channels;

defining a composite channel comprising at least two of the component channels, wherein the user interest score for each component channel in the at least two of the component channels exceeds a predetermined threshold;

determining a composite channel subscription price that is different than a sum of each individual subscription price for each of the component channels included in the composite channel; and

providing a recommendation to a user to subscribe to the composite channel.

19. The method of claim 18 , wherein the recommendation event comprises an activity of the user that is related to consumption of a media item in a content platform.

20. The method of claim 19 , wherein the activity of the user pertains to consumption of the media item that is associated with a component channel to which the user has previously subscribed.

21. The method of claim 19 , wherein the at least two of the component channels are each related to the activity of the user.