Systems and Methods for Determining an Agility Rating Indicating a Responsiveness of an Author to Recommended Aspects for Future Content, Actions, or Behavior

• US 20160078471A1
• Filed: 09/07/2015
• Published: 03/17/2016
• Est. Priority Date: 08/28/2014
• Status: Active Grant

• Current Assignee: Vizit Labs Incorporated
• Original Assignee: Adhark, Inc.
• Inventors: Hamedi, Jehan
• Granted Patent: US 10,242,380 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/90324 using system suggestions
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/1072 Discovery involving ranked list compilation of candidate peers

Abstract

A method includes determining a recommended aspect for future content, action, or behavior. The recommended aspect is determined at least in part based on activity data that indicates aspects of other content authored by or interacted with by a plurality of authors in a social network prior to receipt of the selection. The method also includes providing the recommended aspect for the future content, action, or behavior for a unique author in the social network. The method also includes determining whether the unique author posted the future content, action, or behavior with the recommended aspect in the at least one social network. The method also includes determining, based at least in part on the determination of whether the unique author posted the future content, action, or behavior with the recommended aspect, an agility rating that indicates a responsiveness of the unique author to the recommended aspect.

Claims

1. A system comprising:

a memory; and

a processor coupled to the memory, wherein the processor is configured to;

determine a recommended aspect for future content, action, or behavior, wherein the recommended aspect is determined at least in part based on activity data that indicates aspects of other content authored by or interacted with by a plurality of authors in at least one social network, website, application software, or mobile application software (app) prior to receipt of the selection;

provide the recommended aspect for the future content, action, or behavior for a unique author in the at least one social network, website, application software, or mobile application software (app);

determine whether the unique author posted the future content, took the action, or engaged in the behavior in accordance with the recommended aspect; and

determine, based at least in part on the determination of whether the unique author posted the future content, took the action, or engaged in the behavior in accordance with the recommended aspect, an agility rating that indicates a responsiveness of the unique author to the recommended aspect.

2. The system of claim 1, wherein the agility score is further determined based at least in part on whether the unique author posted a plurality of future contents associated, took a plurality of actions, or engaged in a plurality of behaviors in accordance with a plurality of recommended aspects.

3. The system of claim 2, wherein the agility score is further determined based at least on a predetermined number of the plurality of future contents, actions, or behaviors which occurred most recently in time.

4. The system of claim 2, wherein the agility score is further determined based at least in part on the plurality of future contents, actions, or behaviors, wherein the plurality of future contents, actions, or behaviors have all been posted, taken, or engaged in within a predetermined amount of time from the agility score determination.

5. The system of claim 1, wherein the recommended aspect is at least one of:

a social network, website, application software, or mobile application software (app) in which the future content is recommended to be authored,

a time of day in which the future content is recommended to be authored,

a length that the future content is recommended to be,

a subject matter that the future content is recommended to be related to,

a type of content that the future content is recommended to be,

a tag that the future content is recommended to include,

an indication that the future content is recommended to be lifestyle content or product content,

an indication whether to use paid advertising services on a social network, website, application software, or mobile application software (app) in which the future content is recommended to be authored,

an author to engage with the future content, and

a universal resource indicator (URI) that the future content is recommended to include.

6. A method comprising:

determining, by a processor of a computing device, a recommended aspect for future content, action, or behavior, wherein the recommended aspect is determined at least in part based on activity data that indicates aspects of other content authored by or interacted with by a plurality of authors in at least one social network, website, application software, or mobile application software (app) prior to receipt of the selection;

providing, by the processor, the recommended aspect for the future content, action, or behavior, for a unique author in the at least one social network, website, application software, or mobile application software (app);

determining, by the processor, whether the unique author posted the future content, took the action, or engaged in the behavior in accordance with the recommended aspect; and

determining, by the processor, based at least in part on the determination of whether the unique author posted the future content, took the action, or engaged in the behavior in accordance with the recommended aspect, an agility rating that indicates a responsiveness of the unique author to the recommended aspect.

7. The method of claim 6, further comprising:

monitoring, by the processor, the agility rating of a plurality of users;

determining, by the processor, that a first agility rating of a first user has dropped below a second agility rating of an internal competitor user, external competitor user, or peer user; and

sending, by the processor, an alert message to a computing device of the first user indicating that the first user has been passed in agility rating by the internal competitor user, external competitor user, or peer user.

8. The method of claim 6, further comprising:

monitoring, by the processor, the agility rating of a user;

determining, by the processor, that the agility rating has increased or decreased; and

sending, by the processor, an alert message to a computing device of the user indicating that the agility rating has increased or decreased.

9. The method of claim 6, wherein the agility rating is further determined at least in part based on responsiveness of an internal competitor user, external competitor user, or peer user to the recommended aspect.

10. The method of claim 6, further comprising retrieving, by the processor, the activity data from web pages with a web crawler or API.

11. The method of claim 6, further comprising ranking, by the processor, a plurality of agility ratings corresponding to a plurality of authors.

12. The method of claim 6, further comprising receiving, by the processor, a search criteria, wherein the search criteria specifies a subset of the plurality of authors in the at least one social network, website, application software, or mobile application software (app), wherein the activity data indicates only how the subset of the plurality of authors have responded to the other content.

13. The method of claim 6, wherein the agility rating is further determined at least in part by a fluctuation of content generated by the plurality of authors, wherein the fluctuation is a change in authored content, author action, or author behavior by the plurality of authors occurring over a period of time and with respect to the future content, action, or behavior.

14. The method of claim 6, further comprising determining, by the processor, before the unique author posts the future content, takes the action, or engages in the behavior, how the agility rating will change if the unique author posts the future content, takes the action, or engages in the behavior.

15. The method of claim 6, further comprising determining, by the processor, before the unique author posts the future content, takes the action, or engages in the behavior, what impact the future content, action, or behavior is expected to have if posted, taken, or engaged in.

16. The method of claim 15, further comprising sending, by the processor, to the unique author or an external competitor user, internal competitor user, or peer user of the unique author a message indicating how the agility rating will change if the unique author posts the future content, takes the action, or engages in the behavior.

17. A non-transitory computer readable medium having instructions stored thereon that, upon execution by a computing device, cause the computing device to perform operations comprising:

determining a recommended aspect for future content, action, or behavior, wherein the recommended aspect is determined at least in part based on activity data that indicates aspects of other content authored by or interacted with by a plurality of authors in at least one social network, website, application software, or mobile application software (app) prior to receipt of the selection;

providing the recommended aspect for the future content, action, or behavior for a unique author in the at least one social network, website, application software, or mobile application software (app);

determining whether the unique author posted the future content, took the action, or engaged in the behavior in accordance with the recommended aspect; and

determining, based at least in part on the determination of whether the unique author posted the future content, took the action, or engaged in the behavior in accordance with the recommended aspect, an agility rating that indicates a responsiveness of the unique author to the recommended aspect.

18. The non-transitory computer readable medium of claim 17, wherein the instructions further cause the computing device to perform operations comprising determining a change of a potential future content or scheduled action or behavior on the agility rating in real time as the potential future content is being authored or the action or behavior is being scheduled.

19. The non-transitory computer readable medium of claim 17, wherein the instructions further cause the computing device to perform operations comprising determining an impact of a potential future content or scheduled action or behavior in real time as the potential future content is being authored.

20. The non-transitory computer readable medium of claim 17, wherein the recommended aspect is determined based on how the plurality of authors have responded to the other content in order to optimize a response of the plurality of authors to the future content, action, or behavior.

21. The non-transitory computer readable medium of claim 17, wherein the other content was authored by the unique author.

22. The non-transitory computer readable medium of claim 17, wherein the other content was authored by authors other than the unique author.

23. The non-transitory computer readable medium of claim 17, wherein the other content was authored by a related author to the unique author, and further wherein the related author and the unique author represent competitors for a similar good or service.