Targeted advertising in brick-and-mortar establishments

• US 8,725,567 B2
• Filed: 06/29/2006
• Issued: 05/13/2014
• Est. Priority Date: 06/29/2006
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Huang, Xuedong D., Gates, William H. III, Horvitz, Eric J., Goodman, Joshua T., Brunell, Bradly A., Dumais, Susan T., Flake, Gary W., Griffin, Trenholme J., Hurst-Hiller, Oliver
• Primary Examiner(s): Brown, Alvin L
• Application Number:
  US11/427,761
• Publication Number:
  US 20080004950A1
• Time in Patent Office: 2,875 Days
• Field of Search: 705/14
• US Class Current: 705/14.49
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0271 Personalized advertisement

Abstract

Architecture for presenting advertisements in realtime in retail establishments. A sensor component includes sensors for collecting information about a customer or group of customers as they move through the store. The sensors can include capability for image processing, audio processing, light sensing, velocity sensing, direction sensing, proximity sensing, face recognition, pose recognition, transaction recognition, and biometric sensing, for example. A customer component analyzes the information and generates a profile about the customer. Advertisements are selected for presentation that target the customers as they walk in proximity of a presentation system of the store. An advertisement component facilitates dynamic presentation of a targeted advertisement to the individual as a function of the profile. The customer component can infer information during analysis using machine learning and reasoning.

Claims

1. A computer-implemented system that facilitates presentation of targeted advertisements to an individual, comprising:

a sensor component of a retail establishment that collects sensor information associated with a specific individual proximate to a presentation system;

a customer component that analyzes the sensor information and generates a profile about the specific individual, the customer component further comprising;

an inference component that makes an inference about the specific individual based on some or all of the sensor information collected by the sensor component of the retail establishment as part of generating the profile; and

a storage component that stores historical data of the specific individual and transaction data associated with transactions conducted by the specific individual; and

an advertisement component that facilitates dynamic presentation of a targeted advertisement to the specific individual as a function of the profile.

2. The system of claim 1, wherein the sensor component further facilitates at least one of image processing, audio processing, light sensing, velocity sensing, direction sensing, proximity sensing, face recognition, pose recognition, transaction recognition, or biometric sensing.

3. The system of claim 1, wherein the inference component comprises a machine learning and reasoning system that employs a probabilistic and/or statistical-based analysis to prognose or infer an action that a user desires to be automatically performed.

4. The system of claim 1, wherein the advertising component presents the targeted advertisement via a display proximate to the individual.

5. The system of claim 1, wherein the retail establishment is a brick-and-mortar facility.

6. The system of claim 1, further comprising a presentation system that receives the advertisement from the advertisement component and presents the advertisement for perception by the individual.

7. The system of claim 1, further comprising a personalization component that customizes the advertisement to the individual prior to presentation.

8. The system of claim 1, further comprising a tracking component for tracking interaction behavior of the individual based on the presentation of the advertisement.

9. A computer-implemented method of advertising content to customers of a retail establishment, comprising:

a sensor system comprising one or more sensors, collecting sensor information at the retail establishment about at least one individual of the retail establishment;

processing the sensor information to derive characteristics of the at least one individual, the processing comprising, in part, making inferences about the at least one individual from the sensor information collected at the retail establishment, historical data and transaction data associated with the at least one individual to arrive at the characteristics of the at least one individual;

generating, by a customer component executed at least in part by a processor, a profile for the at least one individual based on the characteristics of the at least one individual;

selecting one or more advertisements for presentation to the at least one individual based on the profile for the at least one individual; and

displaying the one or more advertisements to the at least one individual via a display when the at least one individual is proximate the display.

10. The computer-readable storage media of claim 9, further comprising dynamically streaming the one or more advertisements from a network source to the advertisement component for presentation to the entity.

11. The computer-readable storage media of claim 9, further comprising presenting information to the entity at least one of as the entity approaches the display or as the entity moves away from the display.

12. The computer-readable storage media of claim 9, further comprising presenting article of commerce information on demand by the entity.

13. The computer-readable storage media of claim 9, further comprising modeling knowledge of the entity based on entity interaction.

14. The computer-readable storage media of claim 9, further comprising automatically adjusting pricing of an article of commerce of the retail establishment based on the sensor information that facilitates recognition of one or more entity characteristics.

15. The computer-readable storage media of claim 9, wherein the one or more advertisements selected in the act of selecting are based on preferences of an entity user.

16. The computer-readable storage media of claim 9, further comprising tracking location of the entity utilizing a radio-frequency identification technology.

17. The computer-readable storage media of claim 9, further comprising masking a profile of the entity selectively and dynamically.

18. A method comprising:

collecting, by one or more sensors, sensor information at a brick-and-mortar establishment about a shopping customer of the brick-and-mortar establishment;

processing, by a customer component executed at least in part by a processor, the sensor information to derive customer characteristics, which processing includes, in part, making inferences about the customer from the sensor information collected at the brick-and-mortar establishment, historical data and transaction data associated with the customer to arrive at the customer characteristics;

generating a customer profile based on the customer characteristics;

selecting an advertisement based on the customer profile; and

presenting the advertisement to the customer via a multimedia system when the customer is in perception range of the advertisement as output by the multimedia system.