Methods and systems for predicting content consumption
Methods and systems for content optimization are described. A computing device may determine a predictability score that indicates a probability that a device will access a first content item. The computing device may send a second content item associated with the first content item. The second content item may be based on the predictability score, and the predictability score may be modified. Additional content consumption and/or recommendations may be adjusted based on the predictability score.
1. A system, comprising: a user device configured to access one or more content items and to access a first content item; and a computing device configured to: determine one or more characteristics associated with the one or more content items; determine, based on the one or more characteristics, a predictability score associated with the first content item; send, based on the predictability score, a second content item associated with the first content item; and modify, based on the user device accessing the first content item, the predictability score.
2. The system of claim 1 , wherein the predictability score indicates a probability that the user device will access the first content item and wherein the predictability score is determined using a trained machine learning model, and wherein the predictability score is modified to indicate a higher probability that the user device will access the first content item.
3. The system of claim 1 , wherein the computing device configured to modify the predictability score comprises determining a period of time between sending the second content item and accessing the first content item.
4. The system of claim 1 , wherein the second content item comprises an advertisement for the first content item, and wherein the one or more characteristics indicate at least one of a genre, a title, a subject, one or more actors, one or more directors, a release date, or a viewing date.
5. The system of claim 1 , wherein the computing device is further configured to:
determine, based on the modified predictability score, a third content item associated with a fourth content item, wherein the third content item comprises an advertisement for the fourth content item, and
send the third content item associated with the fourth content item.
6. The system of claim 1 , wherein the computing device is further configured to:
determine, based on viewing data associated with the user device, one or more characteristics associated with the user device; and
determine, based on the one or more characteristics associated with the one or more content items and based on the one or more characteristics associated with the user device, a predictability score for the user device, wherein the predictability score indicates a probability that the user device will access the first content item.
7. The system of claim 6 , wherein the computing device is further configured to:
determine an available content segment associated with the first content item;
determine, based on the predictability score for the user device, an appraisal score associated with the available content segment; and
modify, based on the appraisal score satisfying an appraisal score threshold, the available content segment to indicate the second content item associated with the first content item.
8. A system, comprising:
one or more devices comprising one or more characteristics; and
a computing device configured to:
determine one or more characteristics associated with a first content item;
determine one or more characteristics associated with the one or more devices;
determine, based on the one or more characteristics associated with the first content item and the one or more characteristics associated with the one or more devices, a predictability score for each device of the one or more devices;
based on at least one predictability score satisfying a threshold, send a second content item associated with the first content item to a device of the one or more devices; and
modify, based on the device accessing the first content item, the predictability score.
9. The system of claim 8 , wherein the predictability score indicates a probability that the device will access the first content item and wherein the predictability score is determined using a trained machine learning model, and wherein the predictability score is modified to indicate a higher probability that the device will access the first content item.
10. The system of claim 8 , wherein the computing device is further configured to determine a period of time that the device accessed the first content item.
11. The system of claim 8 , wherein the second content item comprises an advertisement for the first content item, and wherein the one or more characteristics associated with the first content item indicate at least one of a genre, a title, a subject, one or more actors, one or more directors, a release date, or a viewing date.
12. The system of claim 8 , wherein the computing device is further configured to:
determine, based on the modified predictability score, a third content item associated with a fourth content item, wherein the third content item comprises an advertisement for the fourth content item, and
send the third content item associated with the fourth content item.
13. The system of claim 8 , wherein the computing device is further configured to determine, based on one or more content items accessed by each of the one or more devices, a viewing history.
14. The system of claim 8 , wherein the computing device is further configured to:
determine an available content segment associated with the first content item;
determine, based on the predictability score for each device of the one or more devices, an appraisal score associated with the available content segment; and
modify, based on the appraisal score satisfying an appraisal score threshold, the available content segment to indicate the second content item associated with the first content item.
15. One or more non-transitory computer-readable media storing processor-executable instructions that, when executed by at least one processor, cause the at least one processor to:
determine one or more characteristics associated with one or more content items accessed via a device;
determine, based on the one or more characteristics, a predictability score associated with a first content item;
send, based on the predictability score, a second content item associated with the first content item; and
modify, based on the device accessing the first content item, the predictability score.
16. The one or more non-transitory computer-readable media of claim 15 , wherein the predictability score indicates a probability that the device will access the first content item and wherein the predictability score is determined using a trained machine learning model, and wherein the predictability score is modified to indicate a higher probability that the device will access the first content item.
17. The one or more non-transitory computer-readable media of claim 15 , wherein the processor-executable instructions further cause the at least one processor to modify the predictability score comprises determining a period of time between sending the second content item and accessing the first content item.
18. The one or more non-transitory computer-readable media of claim 15 , wherein the second content item comprises an advertisement for the first content item, and wherein the one or more characteristics indicate at least one of a genre, a title, a subject, one or more actors, one or more directors, a release date, or a viewing date.
19. The one or more non-transitory computer-readable media of claim 15 , wherein the processor-executable instructions further cause the at least one processor to:
determine, based on the modified predictability score, a third content item associated with a fourth content item, wherein the third content item comprises an advertisement for the fourth content item, and
send the third content item associated with the fourth content item.
20. The one or more non-transitory computer-readable media of claim 15 , wherein the processor-executable instructions further cause the at least one processor to:
determine, based on viewing data associated with the device, one or more characteristics associated with the device; and
determine, based on the one or more characteristics associated with the one or more content items and based on the one or more characteristics associated with the device, a predictability score for the device, wherein the predictability score indicates a probability that the device will access the first content item.
21. The one or more non-transitory computer-readable media of claim 20 , wherein the processor-executable instructions further cause the at least one processor to:
determine an available content segment associated with the first content item;
determine, based on the predictability score for the device, an appraisal score associated with the available content segment; and
modify, based on the appraisal score satisfying an appraisal score threshold, the available content segment to indicate the second content item associated with the first content item.
22. One or more non-transitory computer-readable media storing processor-executable instructions that, when executed by at least one processor, cause the at least one processor to:
determine one or more characteristics associated with a first content item;
determine one or more characteristics associated with one or more devices;
determine, based on the one or more characteristics associated with the first content item and the one or more characteristics associated with the one or more devices, a predictability score for each device of the one or more devices;
based on at least one predictability score satisfying a threshold, send a second content item associated with the first content item to a device of the one or more devices; and
modify, based on the device accessing the first content item, the predictability score.
23. The one or more non-transitory computer-readable media of claim 22 , wherein the predictability score indicates a probability that the device will access the first content item and wherein the predictability score is determined using a trained machine learning model, and wherein the predictability score is modified to indicate a higher probability that the device will access the first content item.
24. The one or more non-transitory computer-readable media of claim 22 , wherein the processor-executable instructions further cause the at least one processor to determine a period of time that the device accessed the first content item.
25. The one or more non-transitory computer-readable media of claim 22 , wherein the second content item comprises an advertisement for the first content item, and wherein the one or more characteristics associated with the first content item indicate at least one of a genre, a title, a subject, one or more actors, one or more directors, a release date, or a viewing date.
26. The one or more non-transitory computer-readable media of claim 22 , wherein the processor-executable instructions further cause the at least one processor to:
determine, based on the modified predictability score, a third content item associated with a fourth content item, wherein the third content item comprises an advertisement for the fourth content item, and
send the third content item associated with the fourth content item.
27. The one or more non-transitory computer-readable media of claim 22 , wherein the processor-executable instructions further cause the at least one processor to determine, based on one or more content items accessed by each of the one or more devices, a viewing history.
28. The one or more non-transitory computer-readable media of claim 22 , wherein the processor-executable instructions further cause the at least one processor to:
determine an available content segment associated with the first content item;
determine, based on the predictability score for each device of the one or more devices, an appraisal score associated with the available content segment; and
modify, based on the appraisal score satisfying an appraisal score threshold, the available content segment to indicate the second content item associated with the first content item.