SERVING ADVERTISEMENTS BASED ON USER PHYSICAL ACTIVITY

• US 20150154639A1
• Filed: 04/04/2012
• Published: 06/04/2015
• Est. Priority Date: 04/04/2012
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Dupont, Cedric, Williams, Brian Patrick
• Application Number:
  US13/439,424
• Publication Number:
  US 20150154639A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/067 Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0261 based on user location

Abstract

Aspects of the disclosure relate to serving content. In one example, while on a shopping trip at a store, a device may scan for wireless network access point information. The scanned information may be compared to a location model store to determine the device'"'"'s location in the store and how the device is moving through the store. This information may be compared to behavior models. In one example, identifying a behavior model may include comparing the average speed of the device to a single threshold value (faster or slower than this speed?), by comparing the behaviors of the device to a set of pre-determined behavior models (the browser, the list-follower, the single-item purchaser), or by comparing to the device'"'"'s shopping habits. The behavior model may then be used to select and serve content.

Claims

1. A method for generating a set of behavior models for a store, the method comprising:

receiving, by one or more processors, a plurality of time-indexed logs, each time-indexed log of the plurality of being associated with the store and with purchase information describing one or more items purchased by a participant during a shopping trip, and each time-indexed log of the plurality of time-indexed logs including one or more wireless network access point identifiers and signal strengths;

identifying, by the one or more processors, a wireless network access point model for the store, the wireless network access point model mapping locations in the store to wireless network access point identifiers and signal strengths;

for each given time-indexed log of the plurality of time-indexed logs, determining, by the one or more processors, one or more locations, headings, and speeds based on the wireless network access point model;

generating, by one or more processors, the set of behavior models for the store based on the one or more determined locations, headings, and speeds, wherein at least one behavior model of the set of behavior models is generated from time indexed logs of two different participants and includes a speed threshold value;

for the at least one behavior model, generating, by the one or more processors, first and second content information for serving content based on the purchase information associated with the time indexed logs used to generate the at least one behavior model, the first content information being associated with speed values greater than the speed threshold value and the second content information being associated with speed values less than the speed threshold value; and

storing, by the one or more processors, the set of behavior models for the store in memory for later use.

2. The method of claim 1, wherein each of the plurality of time-indexed logs is received from one or more client devices associated with a particular participant, and the method further comprises associating the set of behavior models with an account for the particular user.

3. The method of claim 1, wherein each time-indexed log of the plurality of time-indexed logs further includes measurements from one or more orientation devices, and wherein determining the locations, headings, and speeds for each given time-indexed log of the plurality of time-indexed logs is further based on the measurements from the one or more orientation devices for the given time-indexed log.

4. The method of claim 1, further comprising:

receiving a second plurality of time-indexed logs, each time-indexed log of the second plurality being associated with a second store and purchase information describing items purchased by a participant during a shopping trip to the second store, and each time-indexed log of the plurality of second time-indexed logs including one or more wireless network access point identifiers and signal strengths, wherein the second store is different from the store;

identifying a second wireless network access point model for the second store, the second wireless network access point model mapping locations in the second store to wireless network access point identifiers and signal strengths;

for each given time-indexed log of the plurality of second time-indexed logs, determining one or more second locations, second headings, and second speeds based on the second wireless network access point model;

generating a second set of behavior models for the second store based on the one or more determined second locations, second headings, and second speeds;

for each given behavior model of the second set of behavior models for the store, generating second content information for serving content based on the second purchase information associated with the time-indexed log or time-indexed logs of the plurality of second time-indexed logs used to generate the given behavior model; and

storing the second set of behavior models for the store in the memory for later use.

5. The method of claim 4, further comprising:

receiving, from a first client device, location information;

identifying, from the stored sets of behavior models, the second set of behavior models based on the received location information; and

identifying the second wireless network access point model based on the received location information.

6. The method of claim 5, further comprising:

receiving, from the first client device, a set of time-indexed log entries including wireless network access point identifiers and signal strengths;

after identifying the second wireless network access point model based on the received location information, determining one or more third locations, one or more third headings, and one or more third speeds based on the second wireless network access point model;

identifying a most closely matching behavior model of the second set of behavior models based on the determined one or more third locations, one or more third headings, and one or more third speeds;

identifying content for display to a user based on the second content information associated with the most closely matching behavior model; and

transmitting the identified content to the first client device.

7. A method for selecting content based on physical activity associated with a client device, the method comprising:

receiving, by one or more processors, from the client device, location information;

selecting, by the one or more processors, a set of behavior models from a plurality of stored sets of behavior models based on the received location information, each behavior model of the plurality of behavior models describing behavior of a client device during a shopping event and being associated with content information used to identify content for display to a user;

identifying, by the one or more processors, from a plurality of wireless network access point models, a wireless network access point model based on the received location information, each wireless network access point model of the plurality of wireless network access point models mapping locations in a respective store to wireless network access point identifiers and signal strengths;

receiving, by the one or more processors, from the first client device, a set of time-indexed log entries including one or more wireless network access point identifiers and signal strengths;

determining, by the one or more processors, one or more locations, one or more headings, and one or more speeds based on the identified wireless network access point model;

selecting, by the one or more processors, a most closely matching behavior model of the set of behavior models based on the determined one or more locations, one or more headings, and one or more speeds;

comparing, by the one or more processors, the one or more speeds to a speed threshold value associated with most closely matching behavior model;

identifying, by the one or more processors, content for display to a user of the client device based on the content information associated with the most closely matching behavior model and the comparison; and

transmitting, by the one or more processors, the identified content to the client device.

8. The method of claim 7, wherein identifying the set of behavior models is further based on account information associated with the user of the client device.

9. The method of claim 7, wherein identifying the content is further based on account information associated with the user of the client device indicating how much content the user of the client device wants to receive.

11. The method of claim 7, further comprising:

after identifying content, generating an advertisement from the identified content; and

transmitting the advertisement to the client device.

25. The method of claim 7, wherein the location information describes a type of store and the set of behavior models is selected further based on the type of store.

10. (canceled)

12. A device for generating a set of behavior models for a store, the device comprising:

memory storing instructions;

one or more processors configured to execute the instructions in order to;

receive a plurality of time-indexed logs, each time-indexed log of the plurality of being associated with the store and with purchase information describing one or more items purchased by a participant during a shopping trip, and each time-indexed log of the plurality of time-indexed logs including one or more wireless network access point identifiers and signal strengths;

identify a wireless network access point model for the store, the wireless network access point model mapping locations in the store to wireless network access point identifiers and signal strengths;

for each given time-indexed log of the plurality of time-indexed logs, determine one or more locations, headings, and speeds based on the wireless network access point model;

generate the set of behavior models for the store based on the one or more determined locations, headings, and speeds, wherein at least one behavior model of the set of behavior models is generated from time indexed logs of two different participants and includes a speed threshold value;

for the at least one behavior model, generate first and second content information for serving content based on the purchase information associated the time indexed logs used to generate the at least one behavior model, the first content information being associated with speed values greater than the speed threshold value and the second content information being associated with speed values less than the speed threshold value; and

store the set of behavior models for the store in the memory for later use.

13. The device of claim 12, wherein each of the plurality of time-indexed logs is received from one or more client devices associated with a particular participant, and the processor further associates the set of behavior models with an account for the particular user.

14. The device of claim 12, wherein each time-indexed log of the plurality of time-indexed logs further includes measurements from one or more orientation devices, and wherein the processor further determines the locations, headings, and speeds for each given time-indexed log of the plurality of time-indexed logs is further based on the measurements from the one or more orientation devices for the given time-indexed log.

15. The device of claim 12, wherein the processor further executes the instructions in order to:

receive a second plurality of time-indexed logs, each time-indexed log of the second plurality being associated with a second store and purchase information describing items purchased by a participant during a shopping trip to the second store, and each time-indexed log of the plurality of second time-indexed logs including one or more wireless network access point identifiers and signal strengths, wherein the second store is different from the store;

identify a second wireless network access point model for the second store, the second wireless network access point model mapping locations in the second store to wireless network access point identifiers and signal strengths;

for each given time-indexed log of the plurality of second time-indexed logs, determine one or more second locations, second headings, and second speeds based on the second wireless network access point model;

generate a second set of behavior models for the second store based on the one or more determined second locations, second headings, and second speeds;

for each given behavior model of the second set of behavior models for the store, generate second content information for serving content based on the second purchase information associated with the time-indexed log or time-indexed logs of the plurality of second time-indexed logs used to generate the given behavior model; and

store the second set of behavior models for the store in the memory for later use.

16. The device of claim 15, wherein the processor further executes the instructions in order to:

receive, from a first client device, location information;

identify, from the stored sets of behavior models, the second set of behavior models based on the received location information; and

identify the second wireless network access point model based on the received location information.

17. The device of claim 16, wherein the processor further executes the instructions in order to:

receive, from the first client device, a set of time-indexed log entries including wireless network access point identifiers and signal strengths;

after identifying the second wireless network access point model based on the received location information, determine one or more third locations, one or more third headings, and one or more third speeds based on the second wireless network access point model;

identify a most closely matching behavior model of the second set of behavior models based on the determined one or more third locations, one or more third headings, and one or more third speeds;

identify content for display to a user based on the second content information associated with the most closely matching behavior model;

transmit the identified content to the first client device.

18. A device for selecting content based on physical activity associated with of a client device, the device comprising:

memory storing instructions;

one or more processors configured to execute the instructions in order to;

receive, from the client device, location information;

identifying a set of behavior models from a plurality of stored sets of behavior models based on the received location information, each behavior model of the plurality of behavior models describing behavior of a client device during a shopping event and being associated with content information used to identify content for display to a user;

identify, from a plurality of wireless network access point models, a wireless network access point model based on the received location information, each wireless network access point model of the plurality of wireless network access point models mapping locations in a respective store to wireless network access point identifiers and signal strengths;

receive, from the first client device, a set of time-indexed log entries including one or more wireless network access point identifiers and signal strengths;

determine one or more locations, one or more headings, and one or more speeds based on the identified wireless network access point model;

select a most closely matching behavior model of the second set of behavior models based on the determined one or more locations, one or more headings, and one or more speeds;

comparing the one or more speeds to a speed threshold value associated with the behavior model;

identify content for display to a user of the client device based on the content information associated with the most closely matching behavior model and the comparison; and

transmit the identified content to the client device.

19. The device of claim 18, wherein the processor further executes the instructions in order to identify the set of behavior models based on account information associated with the user of the client device.

20. The device of claim 18, wherein the processor further executes the instructions in order to identify the content based on account information associated with the user of the client device indicating how much content the user of the client device wants to receive.

21. The device of claim 18, wherein the processor further executes the instructions in order to identify the content based on account information associated with the user of the client device indicating how much content the user of the client device wants to receive.

22. The device of claim 18, wherein the processor further executes the instructions in order to:

after identifying content, generate an advertisement from the identified content; and

transmit the advertisement to the client device.

23. A tangible, non-transitory computer-readable storage medium on which computer readable instructions of a program are stored, the instructions, when executed by a processor, cause the processor to perform a method of generating a set of behavior models for a store, the method comprising:

receiving a plurality of time-indexed logs, each time-indexed log of the plurality of being associated with the store and with purchase information describing one or more items purchased by a participant during a shopping trip, and each time-indexed log of the plurality of time-indexed logs including one or more wireless network access point identifiers and signal strengths;

identifying a wireless network access point model for the store, the wireless network access point model mapping locations in the store to wireless network access point identifiers and signal strengths;

for each given time-indexed log of the plurality of time-indexed logs, determining one or more locations, headings, and speeds based on the wireless network access point model;

generating the set of behavior models for the store based on the one or more determined locations, headings, and speeds, wherein at least one behavior model of the set of behavior models is generated from time indexed logs of two different participants and includes a speed threshold value;

for the at least one behavior model, generating first and second content information for serving content based on the purchase information associated with the time indexed logs used to generate the at least one behavior model, the first content information being associated with speed values greater than the speed threshold value and the second content information being associated with speed values less than the speed threshold value; and

storing the set of behavior models for the store in memory for later use.

24. A tangible, non-transitory computer-readable storage medium on which computer readable instructions of a program are stored, the instructions, when executed by a processor, cause the processor to perform a method of selecting content based on physical activity associated with of a client device, the method comprising:

receiving, from the client device, location information;

identifying a set of behavior models from a plurality of stored sets of behavior models based on the received location information, each behavior model of the plurality of behavior models describing behavior of a client device during a shopping event and being associated with content information used to identify content for display to a user;

identifying, from a plurality of wireless network access point models, a wireless network access point model based on the received location information, each wireless network access point model of the plurality of wireless network access point models mapping locations in a respective store to wireless network access point identifiers and signal strengths;

receiving, from the first client device, a set of time-indexed log entries including one or more wireless network access point identifiers and signal strengths;

determining one or more locations, one or more headings, and one or more speeds based on the identified wireless network access point model;

selecting a most closely matching behavior model of the second set of behavior models based on the determined one or more locations, one or more headings, and one or more speeds;

comparing the one or more speeds to a speed threshold value associated with the behavior model;

identifying content for display to a user of the client device based on the content information associated with the most closely matching behavior model and the comparison; and

transmitting the identified content to the client device.