TARGETED ADVERTISING IN BRICK-AND-MORTAR ESTABLISHMENTS

• US 20080004950A1
• Filed: 06/29/2006
• Published: 01/03/2008
• Est. Priority Date: 06/29/2006
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Dumais, Susan T., Flake, Gary W., Huang, Xuedong D., Goodman, Joshua T., Hurst-Hiller, Oliver, Griffin, Trenholme J., Horvitz, Eric J., Brunell, Bradly A., Gates, William H.
• Granted Patent: US 8,725,567 B2
• Time in Patent Office: Days
• US Class Current: 705/14
• 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 an individual proximate to a presentation system;

a customer component that analyzes the sensor information and generates a profile about the individual; and

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

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

3. The system of claim 1, further comprising an inference component that makes an inference about some or all of the sensor information as a part of generating the profile.

4. The system of claim 3, 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.

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

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

7. 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.

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

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

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

collecting sensor information about a shopping entity of the retail establishment;

processing the sensor information to derive entity characteristics, which processing includes, in part, making inferences about the sensor information to arrive at the entity characteristics;

generating an entity profile for the entity based on the entity characteristics;

selecting one or more advertisements for presentation to the entity based on the entity profile; and

displaying the one or more advertisements to the entity via a display when the entity is proximate the display.

11. The method of claim 10, further comprising dynamically streaming the one or more advertisements from a network source to the advertisement component for presentation to the entity.

12. The method of claim 10, wherein the shopping entity is a group of individuals.

13. The method of claim 10, further comprising presenting information to the entity at least one of as the entity approaches the display and as the entity moves away from the display.

14. The method of claim 10, further comprising presenting article of commerce information on demand by the entity.

15. The method of claim 10, further comprising modeling knowledge of the entity based on entity interaction.

16. The method of claim 10, further comprising an act of 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.

17. The method of claim 10, wherein the one or more advertisements selected in the act of selecting are based on preferences of an entity user.

18. The method of claim 10, further comprising tracking location of the entity utilizing a radio-frequency identification technology.

19. The method of claim 10, further comprising masking a profile of the entity selectively and dynamically.

20. A computer-executable system, comprising:

computer-implemented means for collecting sensor information about a shopping customer of a brick-and-mortar establishment;

computer-implemented means for processing the sensor information to derive customer characteristics, which processing includes, in part, making inferences about the sensor information to arrive at the customer characteristics;

computer-implemented means for generating a customer profile based on the customer characteristics;

computer-implemented means for selecting an advertisement based on the customer profile; and

computer-implemented means for 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.