DETERMINATION AND MONETIZATION OF FUTURE LOCATION

• US 20130006777A1
• Filed: 07/01/2011
• Published: 01/03/2013
• Est. Priority Date: 07/01/2011
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Chand, Ashootosh, Krishnareddy, Suresh Kumar
• Granted Patent: US 9,947,014 B2
• Time in Patent Office: Days
• US Class Current: 705/14.66
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0261 based on user location

Abstract

A computer-implemented method for monetizing future location of users includes identifying indicator(s) retrieved from log data or an electronic declaration that indicate a possibility that a user will be at a specific location in the future; generating a probability that the user will be at the specific location in the future based on the indicator(s); and charging an advertiser a cost for an impression to which to serve a location-specific advertisement targeted to the user, the cost charged being greater when the probability is greater that the user will be at the specific location in the future. The method may be extended to targeting a group of users that expect to be at the same location at the future point in time. Monetization of future locations may depend on the quality and/or quantity of the log data and declarations of future locations and on a number of users in a group of users if monetized according to the group.

Claims

1. A method for monetizing future location of one or more users, the method executable by a computer coupled with a processor and data storage, the method comprising:

identifying, by the processor, one or more indicators retrieved from log data or an electronic declaration that indicate a possibility that a user will be at a specific location at a future point in time;

generating, by the processor, a probability that the user will be at the specific location at the future point in time based on the one or more indicators; and

charging, by the computer, an advertiser a cost for an impression to which to serve a location-specific advertisement targeted to the user, the cost charged being greater when the probability is greater that the user will be at the specific location at the future point in time.

2. The method of claim 1, where the probability is based on one or more indicators selected from the group consisting of:

a current location of the user;

a location history of the user; and

a history of adherence to electronic declarations of a future location.

3. The method of claim 2, where the electronic declaration of the future location comprises detecting the user sending or accepting a calendar invitation for an event at the future location.

4. The method of claim 1, where the probability is based on one or more activities or events in which the user participates or has made plans to participate.

5. The method of claim 1, where the probability is based on the user booking one or more services selected from the group consisting of a hotel room, an airline ticket, and a venue at the specific location, the probability increasing when more than one service is booked.

6. The method of claim 1, further comprising:

determining in which of a plurality of probability ranges the probability resides; and

charging the cost based on the probability range in which the probability resides, the cost being increased in higher probability ranges.

7. The method of claim 1, further comprising:

determining an incremental ad rate per user for a group of users having a probability within a specific probability range, the group of users to which the location-specific advertisement will be targeted, where the ad rate per user is increased for a larger group of users; and

charging a cost to the advertiser calculated as the ad rate times the number of users for serving the location-specific advertisements to the group of users.

8. The method of claim 1, where a future location of the user is determined from one or a combination of the following:

a default location that the user personalizes and can update anytime;

saved locations affiliated with common locations selected from the group consisting of home, work, and school; and

queried locations related to one or more database or search engine queries entered by the user.

9. A system for monetizing future location of one or more users, comprising:

a computer including a processor and system storage;

at least one database stored in the system storage in which is stored log data;

the processor operable to;

identify one or more indicators retrieved from the log data or from other data associated with a user that indicate a probability that a user will be at a specific location in the future;

generate a quality score based on the one or more indicators, where the quality score is higher for better quality data or stronger indicators that the user will be at the specific location in the future; and

charge an advertiser a cost for an impression to which to serve a location-specific advertisement targeted to the user, the cost charged varying with the quality score.

10. The system of claim 9, where the quality score is higher based on a current location of the user that is closer to the specific location as compared with being farther away;

and where the quality score is higher for indicators that the user will be at the specific location in the near future.

11. The system of claim 9, where the quality score is higher based on a past history of the user frequenting the specific location as compared with a history of rarely visiting the specific location.

12. The system of claim 9, where the quality score is higher based on one or more declarations of future location that is within a predetermined distance of the specific location as compared with an absence of, or fewer, declarations of future location within the predetermined distance of the specific location.

13. The system of claim 12, where the declaration of future location comprises the user booking one or a combination of a hotel room, an airline ticket, and a venue at or near the specific location, the quality score increasing with the number of bookings.

14. The system of claim 9, where the quality score is higher for a declaration of future location of a close friend of the user in a social network when compared with a friend of a friend.

15. The system of claim 9, the processor future operable to:

determine in which of a plurality of ranges the quality score resides; and

charging the cost based on the range in which the quality score resides, the cost being increased in higher ranges of the quality score.

16. The system of claim 9, the processor future operable to:

determine an incremental ad rate per user for a group of users having a quality score within a specific range, the group of users to which the location-specific advertisement will be targeted, where the ad rate per user is increased for a larger group of users; and

charge a cost to the advertiser calculated as the ad rate times the number of users for serving the location-specific advertisements to the group of users.

17. The system of claim 9, where a future location of the user is determined from one or a combination of the following:

a default location that the user personalizes and can update anytime;

saved locations affiliated with common locations selected from the group consisting of home, work, and school; and

queried locations related to one or more database or search engine queries entered by the user.

18. A method for monetizing future location of groups of users, the method executable by a computer coupled with a processor and data storage, the method comprising:

identifying, by the processor, one or more indicators retrieved from log data or an electronic declaration that indicate a probability that two or more users will be at a specific location at a future point in time;

generating, by the processor, a plurality of quality scores, one for each of at least two of the two or more users, the quality scores based on how likely it is that each user will be at the specific location at the future point in time based on the one or more indicators; and

determining, by the processor, a cost per user for a group of users in a range of quality score percentiles, the cost per user depending on the range of quality score percentiles of the group and on how many users are in the group.

19. The method of claim 18, where the two or more users comprise a group of users sharing social connections.

20. The method of claim 18, further comprising:

charging, by the computer, an advertiser a cost for a group of impressions to which to serve a location-specific advertisement targeted to the group of users, the cost charged being greater when the quality score percentiles in the range of quality score percentiles are greater and also when the number of users in the group of users is greater.

21. The method of claim 20, where the location-specific advertisement targets a group of users that share a social circle, the location-specific advertisement addressing subject matter of common interest among at least some of the group of users.

22. The method of claim 18, where the quality score of each user is based at least in part on bulk booking as a group of users one or more services selected from the group consisting of a flight;

a hotel;

a restaurant; and

another venue, where the quality score is higher for each user for each additional service that was booked as a group, and where the group of users share common social connections.

23. The method of claim 18, where a future location of the two or more users is determined from one or a combination of the following:

a default location that each user personalizes and can update anytime;

saved locations affiliated with common locations selected from the group consisting of home, work, and school; and

queried locations related to one or more database or search engine queries entered by each user.