Systems and methods for determining and displaying optimal associations of data items
Systems and methods are described for determining and displaying optimal associations of data items. Data items may include media content such as television programs, and may be associated with advertisements to be displayed during content consumption. A tool may process data regarding segments of viewers that have common characteristics, and further process data regarding viewers of particular data items, to identify degrees of association between individual segments of viewers and particular data items. The degrees of association between a particular data item and multiple segments of viewers, or between multiple data items and a particular segment of viewers, may be displayed in a user interface that identifies optimal associations between data items and advertisements based on the viewer segments having high degrees of association with the data item.
1. A system comprising:
a data store configured to store computer-executable instructions; and
a processor in communication with the data store, wherein the computer-executable instructions, when executed by the processor, configure the processor to perform operations including:
accessing first data identifying a plurality of segments of consumers of media content;
accessing second data identifying a plurality of consumers of media content, wherein individual consumers in the plurality of consumers of media content consumed a content item from a specified source;
determining, based at least in part on the plurality of segments of consumers and the plurality of consumers, a degree of association between individual content items and a characteristic associated with each consumer in a first segment of consumers; and
causing display of a user interface that enables selection of one or more characteristics associated with consumers, wherein the user interface includes the degree of association between the selected one or more characteristics and one or more content items.
2. The system of claim 1 , wherein each segment in the plurality of segments of consumers of media content corresponds to a respective characteristic associated with individual consumers in the segment.
3. The system of claim 2 , wherein the respective characteristic is associated with each consumer in the segment.
4. The system of claim 1 , wherein the individual consumers in the plurality of consumers of media content consumed the content item from the specified source at a first date and time.
5. The system of claim 1 , wherein the individual consumers in the plurality of consumers of media content consumed the content item from the specified source at one of a plurality of dates and times.
6. The system of claim 1 , wherein the data store is configured to store further computer-executable instructions that, when executed by the processor, configure the processor to perform further operations including generating the user interface.
7. A computer-implemented method comprising:
obtaining first data identifying a plurality of segments of consumers of media content;
obtaining second data identifying a plurality of consumers of media content, wherein individual consumers in the plurality of consumers of media content consumed a content item from a specified source;
determining, based at least in part on the plurality of segments of consumers and the plurality of consumers, a degree of association between individual content items and a characteristic associated with each consumer in a first segment of consumers; and
causing display of a user interface that enables selection of one or more characteristics associated with consumers, wherein the user interface includes the degree of association between the selected one or more characteristics and one or more content items.
8. The computer-implemented method of claim 7 , wherein the user interface enables selection of a plurality of viewing time categories.
9. The computer-implemented method of claim 8 , wherein the plurality of viewing time categories includes one or more of a “live” category, “live+same day” category, “live+3 days” category, or “live+7 days” category.
10. The computer-implemented method of claim 7 , wherein the user interface includes an estimated size of one or more segments of the plurality of segments of consumers of media content.
11. The computer-implemented method of claim 7 , wherein the user interface includes information that enables mapping of individual consumers in the second data to corresponding portions of the first data.
12. The computer-implemented method of claim 7 , wherein the degree of association between individual content items and the characteristic associated with each consumer in the first segment of consumers is determined based at least in part on an amount of minutes viewed by individual consumers of the individual content item.
13. The computer-implemented method of claim 7 further comprising determining, based at least in part on the plurality of segments of consumers and the plurality of consumers, a degree of association between individual timeslots and a characteristic associated with each consumer in a first segment of consumers.
14. The computer-implemented method of claim 13 , wherein the user interface enables selection of one or more timeslots.
15. The computer-implemented method of claim 7 further comprising determining, based at least in part on the plurality of segments of consumers and the plurality of consumers, a degree of association between the specified source and a characteristic associated with each consumer in a first segment of consumers.
16. The computer-implemented method of claim 15 , wherein the user interface enables selection of one or more sources.
17. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a processor, configure the processor to perform operations including:
determining, based at least in part on first data identifying a plurality of segments of consumers of content items and second data identifying a plurality of consumers of content items, a degree of association between individual content items and a characteristic associated with each consumer in a first segment of consumers; and
causing display of a user interface that enables selection of one or more characteristics associated with consumers, wherein the user interface includes the degree of association between the selected one or more characteristics and one or more content items.
18. The non-transitory computer-readable medium of claim 17 , wherein individual consumers in the plurality of consumers of content items consumed a content item from a specified source.
19. The non-transitory computer-readable medium of claim 17 , wherein at least one of the first data or the second data is obtained from a plurality of data sources.
20. The non-transitory computer-readable medium of claim 19 , wherein the user interface enables selection from the plurality of data sources.