HARNESSING LARGE DATA SOURCES TO DEFINE A MOBILE USER'S REAL-TIME CONTEXT THEN DETERMINING AND DELIVERING HIGHLY RELEVANT MOBILE MESSAGES BASED ON THAT CONTEXT

• US 20140344050A1
• Filed: 05/13/2014
• Published: 11/20/2014
• Est. Priority Date: 05/16/2013
• Status: Abandoned Application

• Current Assignee: Kochava, Inc.
• Original Assignee: MobileRQ, Inc. (Kochava, Inc.)
• Inventors: Lonchar, Bart, McKinley, Tyler, Glatt, Darin
• Application Number:
  US14/276,718
• Publication Number:
  US 20140344050A1
• Time in Patent Office: Days
• US Class Current: 705/14.45
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0246 Traffic
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 30/0267 Wireless devices
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

Embodiments described herein relate generally to receiving information from a mobile device and selecting content to be provided to that mobile device based on the received information. An audience may be identified that is to include the mobile device and/or a user thereof based on the information received from the mobile device. The identified audience may be associated with a campaign. Accordingly, content also associated with the campaign may be identified. This content may be sent to a mobile device associated with the user. A relevancy value may be calculated to indicate whether the content should be provided to the mobile device. If the relevancy value does not meet or exceed a predetermined threshold, then the content may not be provided to the mobile device. Other embodiments may be described and/or claimed.

Claims

1. A computing device for delivery of content by marketers to users of mobile devices, the computing device comprising:

an information intake module to process context information to be received over a network from a first mobile device associated with a user;

a content selection engine, coupled to the information intake module, to identify, based on the context information, an audience, associated with a campaign, that is to include the mobile device, and to identify content associated with the campaign; and

a content delivery module, coupled to the content selection engine, to generate a message to provide the identified content to a second mobile device associated with the user.

2. The computing device of claim 1, wherein the first and second mobile devices are a same mobile device.

3. The computing device of claim 1, wherein the context information is to include an indication of at least one of an attribute of the mobile device, a location associated with the mobile device, or an application of the mobile device associated with provision of the context information.

4. The computing device of claim 3, wherein the context information is to include an itinerary having an indication of a flight, and at least one of an origin of the flight, a destination of the flight, a time of departure of the flight, a time of arrival of the flight.

5. The computing device of claim 1, further comprising:

an information definition module, coupled with the content selection engine, to provide a user interface over a network, to process data received through the user interface and to define the audience or the campaign based on the data.

6. The computing device of claim 1, wherein the audience includes one or more predicates, the context information includes one or more features, and the content selection engine is to:

identify the audience based on a determination that each of the one or more predicates is met by a corresponding feature of the one or more features.

7. The computing device of claim 6, wherein each of the one or more predicates is associated with a value and the content delivery module is to:

calculate a relevance value associated with the campaign based on the values of the one or more predicates; and

generate the message based on a determination that the relevance value meets or exceeds a predetermined threshold.

8. The computing device of claim 7, wherein the content selection engine is to identify another audience based on the context information, to identify another campaign based on the other audience, and to identify another content based on the other campaign, and further wherein the content delivery module is to calculate another relevance value based on the values of one or more predicates included in the other audience, to generate another message based on the other content, and provide, to the mobile device, the first message, the other message, a first indication of the first relevance value, and another indication of the other relevance value.

9. The computing device of claim 7, wherein the information intake module is further to supplement the context information with metadata, the content selection engine is to identify the audience further based on the metadata and to calculate the relevance value further based on the metadata.

10. The computing device of claim 9, wherein the metadata is to include an indication of at least one of weather information, an origin, a destination, an estimated departure time of a flight, an actual departure time of the flight, an estimated arrival time of the flight, an actual arrival time of the flight, a duration of the flight, a status of the flight, a name of a hotel, an address of a location, and a type of location.

11. The computing device of claim 10, wherein the information intake module is additionally coupled with one or more databases, and further wherein the information intake module is to process data received from the one or more databases and to supplement the context information with the metadata based on the data received from the one or more databases.

12. The computing device of claim 11, wherein the information intake module is to process fresh data received from the one or more databases that updates the first data received from the one or more databases, and further wherein the content selection engine is to identify updated content based on the fresh data.

13. The computing device of claim 1, wherein the content delivery module is further to determine that the identified content is no longer relevant to the mobile device and to provide, to the mobile device, an indication that the identified content is no longer relevant to the mobile device.

14. The computing device of claim 1, further comprising:

an analytics module, coupled to the content selection engine, to store information associated with at least one of the context information, the audience, the campaign, and the content, and to provide analytical information based on the stored information.

15. The computing device of claim 14, wherein the analytics module is further to identify a potential audience based on the information received from the mobile device associated with the user and provide an indication of the identified potential audience to a marketer.

16. A computer-implemented method for delivery of content by marketers to users of mobile devices, the method comprising:

receiving, from a mobile device, information associated with the mobile device or a user of the mobile device;

identifying content based on the information received from the mobile device;

computing a relevancy value associated with the content; and

sending the content to the mobile device only where the computed relevancy value meets or exceeds a predetermined threshold.

17. The computer-implemented method of claim 16, further comprising:

identifying second content based on the information received from the mobile device;

computing a second relevancy value associated with the second content;

determining an order of the first content and the second content based on the first relevancy value and the second relevancy value;

sending the second content and an indication of the order to the mobile device only where the second computed relevancy value meets or exceeds the predetermined threshold.

18. The computer-implemented method of claim 16, wherein computing the relevancy value comprises:

identifying one or more features based on the information received from the mobile device that match one or more predicates associated with the identifying of the content, each predicate of the one or more predicates to be associated with a respective weighting value; and

computing the relevancy value based on the one or more weighting values associated with the one or more predicates that match the one or more features.

19. The computer-implemented method of claim 16, wherein the user of the mobile device is a traveler and the content is associated with at least one of a flight the traveler is to take, an airline provider of the flight, and a hotel at which the traveler is to stay.

20. The computer-implemented method of claim 19, wherein the identifying of the content is further based on one or more updates associated with at least one of the flight, the airline provider, and the hotel, and the method further comprising:

receiving, over a network, the one or more updates.

21. The computer-implemented method of claim 16, further comprising:

determining that the content sent to the mobile device is no longer relevant to the mobile device; and

sending an indication to the mobile device that the content is no longer relevant.

22. The computing-implemented method of claim 16, further comprising:

providing, over a network, an interface for a marketer;

receiving, through the interface, data that is to identify one or more predicates to be matched with the information to be received from the mobile device for the identifying of the content.

23. The computer-implemented method of claim 22, further comprising:

receiving, from the marketer over the network, an indication of whether the content should be provided to the mobile device based on a request to be received from the mobile device;

receiving, from the mobile device, a request for the content; and

providing the content to the mobile device based on the request.

24. The computer-implemented method of claim 16, wherein the sending the content to the mobile device comprises:

generating a message that includes the content and one or more variables to be resolved by the mobile device; and

sending the message to the mobile device only where the computed relevancy value indicates that the content is relevant to the mobile device.

25. The computer-implemented method of claim 16, further comprising:

identifying a potential group to be provided content based on the received information associated with the mobile device or the user of the mobile device; and

providing an indication of the identified potential group to a marketer over a network.

26. The computer-implemented method of claim 16, further comprising:

notifying a partner marketer that the mobile device is available to receive content based on the received information associated with the mobile device or the user of the mobile device.

27. The computer-implemented method of claim 16, further comprising:

receiving an indication of user interaction or absence of user interaction with the content sent to the mobile device; and

sending additional content to the mobile device associated with the user based on the indication of the user interaction or the absence of user interaction.

28. One or more non-transitory computer system-readable media comprising computing device-executable instructions, wherein the instructions, in response to execution by a computing device, cause the computing device to:

receive, from a mobile device, information associated with the mobile device or a user of the mobile device;

identify content based on the information received from the mobile device;

compute a relevancy value associated with the content; and

send the content to the mobile device only where the computed relevancy value meets or exceeds the predetermined threshold.

29. The one or more non-transitory computer system-readable media of claim 28, wherein the instructions, in response to execution by the computing device, further cause the computing device to:

identify second content based on the information received from the mobile device;

compute a second relevancy value associated with the second content;

determine an order of the first content and the second content based on the first relevancy value and the second relevancy value;

send the second content and an indication of the order to the mobile device only where the second computed relevancy value meets or exceeds a predetermined threshold value.

30. The one or more non-transitory computer system-readable media of claim 28, wherein the instructions, in response to execution by the computing device, further cause the computing device to:

gather information associated with one or more of the mobile device, the content, the user, and a marketer of the content;

compute analytical information based on the gathered information; and

provide the computed analytical information to the marketer over a network.

31. The one or more non-transitory computer one or more non-transitory computer system-readable media of claim 28, wherein the content is to include actual instruction content to cause an automated response at the mobile device.

32. The one or more non-transitory computer system-readable media of claim 28, wherein the content is to include reference instruction content that corresponds to actual instruction content, and further wherein the instructions, in response to execution by the computing device, further cause the computing device to:

process an indication, received from the mobile device, that the mobile device has detected a user interaction associated with the reference instruction content; and

provide actual instruction content to the mobile device based on the indication.