Systems and methods to determine reduction of interest in a content series

1. A method comprising:

monitoring consumption of a content series, the consumption associated with a profile;

determining a pattern of consumption of the content series associated with the profile;

determining, based on the pattern of consumption, an expected amount of consumption associated with the profile during a time period;

determining a change in the pattern of consumption during the time period indicative of a reduction of interest in the content series by determining that a first amount of consumption during the time period is less than the expected amount of consumption during the time period;

identifying contextual information related to the content series based at least in part on the change in the pattern of consumption, wherein the contextual information comprises information about the content series during the time period when the change in the pattern of consumption was determined;

determining a reason for the reduction of interest based at least in part on the contextual information and the change in the pattern of consumption;

in response to determining the reason for the reduction of interest, displaying a first piece of content, wherein the first piece of content relates to the determined reason; and

transmitting the determined reason to a device.

2. The method of claim 1 , wherein determining the pattern of the consumption of the content series comprises determining a frequency of consumption during the time period.

3. The method of claim 1 , wherein determining the change in the pattern consumption comprises using a trained machine learning model to identify the change in the pattern of consumption.

4. The method of claim 1 , wherein the information about the content series comprises at least one of a change in plot of the content series, a change in actors of the content series, a change in production of the content series, or a change in schedule of the content series.

5. The method of claim 1 , wherein the device is a first server.

6. The method of claim 5 , wherein the monitoring is performed by a second server and the second server transmits the determined reason to the first server.

7. An apparatus comprising:

control circuitry; and

at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the control circuitry, cause the apparatus to perform at least the following:

monitor consumption of a content series, the consumption associated with a profile;

determine a pattern of consumption of the content series associated with the profile;

determine based on the pattern of consumption, an expected amount of consumption associated with the profile during a time period;

determine a change in the pattern of consumption during the time period indicative of a reduction of interest in the content series by determining that a first amount of consumption during the time period is less than the expected amount of consumption during the time period;

identify contextual information related to the content series based at least in part on the change in the pattern of consumption, wherein the contextual information comprises information about the content series during the time period when the change in the pattern of consumption was determined;

determine a reason for the reduction of interest based at least in part on the contextual information and the change in the pattern of consumption;

in response to determining the reason for the reduction of interest, display a first piece of content, wherein the first piece of content relates to the determined reason; and

transmit the determined reason to a device.

8. The apparatus of claim 7 , wherein the apparatus is further caused, when determining the pattern of the consumption of the content series, to determine a frequency of consumption during the time period.

9. The apparatus of claim 7 , wherein the apparatus uses a trained machine learning model to identify the change in the pattern of consumption.

10. The apparatus of claim 7 , wherein the information about the content series comprises at least one of a change in plot of the content series, a change in actors of the content series, a change in production of the content series, or a change in schedule of the content series.

11. The apparatus of claim 7 , wherein the device is a first server.

12. The apparatus of claim 11 , wherein the apparatus is a second server.

13. A non-transitory computer-readable medium having instructions encoded thereon that, when executed by control circuitry, cause the control circuitry to:

monitor consumption of a content series, the consumption associated with a profile;

determine a pattern of consumption of the content series associated with the profile;

determine based on the pattern of consumption, an expected amount of consumption associated with the profile during a time period;

determine a change in the pattern of consumption during the time period indicative of a reduction of interest in the content series by determining that a first amount of consumption during the time period is less than the expected amount of consumption during the time period;

identify contextual information related to the content series based at least in part on the change in the pattern of consumption, wherein the contextual information comprises information about the content series during the time period when the change in the pattern of consumption was determined;

determine a reason for the reduction of interest based at least in part on the contextual information and the change in the pattern of consumption;

in response to determining the reason for the reduction of interest, display a first piece of content, wherein the first piece of content relates to the determined reason; and

transmit the determined reason to a device.

14. The non-transitory computer-readable medium of claim 13 , wherein the control circuitry is further caused, when determining the pattern of the consumption of the content series, to determine a frequency of consumption during the time period.

15. The non-transitory computer-readable medium of claim 13 , wherein the control circuitry uses a trained machine learning model to identify the change in the pattern of consumption.

16. The non-transitory computer-readable medium of claim 13 , wherein the information about the content series comprises at least one of a change in plot of the content series, a change in actors of the content series, a change in production of the content series, or a change in schedule of the content series.

17. The non-transitory computer-readable medium of claim 13 , wherein the device is a server.