PROCESS AND SYSTEM FOR TARGETING OF CONTENT TO SEGMENTED CUSTOMER BASE

• US 20080306820A1
• Filed: 12/06/2007
• Published: 12/11/2008
• Est. Priority Date: 12/06/2006
• Status: Abandoned Application

• Current Assignee: Calder Group Incorporated
• Original Assignee: Calder Group Incorporated
• Inventors: Passmore, Eric
• Application Number:
  US11/952,057
• Publication Number:
  US 20080306820A1
• 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 30/0255 based on user history
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

A method and system for targeted in-store advertising content is disclosed. In order to improve the success of advertising content on a group of customers, the present invention monitors and records items as they are purchased from the store. These records generate data that is used to categorize customers into defined segments. Segments are matched to pre-defined profiles, which describe certain demographic characteristics common to customers in a particular segment. Advertisers can create advertising campaigns directed to these profiles, and when a certain number of matching segments appear within a certain amount of time within the store, the present invention will display the matching media content. The present invention tracks segment frequency, and applies a weighted T-distribution analysis to determine the likelihood of certain frequencies of segments appearing at a certain time. The present invention also tracks the number of times certain media content has been displayed within a certain amount of time to prevent content overexposure. Use of the present invention'"'"'s data will help advertisers by introducing a pay for performance model where advertisers pay to deliver content to their target demographic, and by providing information on whether or not an advertising campaign was successful.

Claims

1. A method comprising:

identifying an item purchased by a first customer;

categorizing the first customer into a first segment, the first segment based upon the item purchased by the customer;

matching the first segment with a pre-determined profile; and

displaying previously-stored advertising content associated with the pre-determined profile.

2. The method of claim 1, further comprising adding additional product information before categorizing the customer into a segment;

and using the additional product information to categorize the customer into a segment.

3. The method of claim 1, further comprising:

recording first temporal data during the identification step for the item purchased by the first customer;

recording second temporal data point the identification step for an item purchased by a second customer, the second customer categorized in the same segment as the first customer; and

applying a probability distribution to the first and second temporal data point to determine a confidence rating, the confidence rating representing the likelihood that a third customer will purchase an item, resulting in the third customer being categorized in a third segment that is the same as the first customer'"'"'s segment.

4. The method of claim 1, further comprising:

defining a time interval;

defining a content frequency limit;

counting how many times the previously-stored advertising content is displayed within the defined time interval;

ceasing display of the previously-stored advertising content once the counting step reaches a limit the content frequency limit within the time interval; and

displaying previously-stored advertising content not associated with the pre-determined profile.

5. The method of claim 1, further comprising:

providing an item promotional code to the customer after purchase; and

monitoring for use of the promotional code.

6. The method of claim 4, further comprising recording data, the data including information on the date and time the item promotional code was provided, and the date and time the item promotional code was used.

7. A system comprising:

a shopping basket monitor software module that collects data on at least one item purchased by at least one customer, the shopping basket monitor software module stored in a memory device;

a profile analysis software module that uses the collected data from the shopping basket monitor module and categorizes the customer into a segment based upon the data, and then matches the segment to a pre-defined profile, the profile analysis software module stored in a memory device;

a content database that contains at least one previously-stored advertising content file matching at least one profile, the advertiser database stored in a memory device;

a content delivery software module that transmits, to a display device, advertising content matched to at least one profile, the content delivery software module stored in a memory device; and

a display device that displays advertising content transmitted from the content delivery software module.

8. The system of claim 7, wherein the content delivery software module uses a confidence rating to match previously stored content to at least one segment.

9. The system of claim 7, wherein the content delivery software module charges different fees for advertising content transmitted with different confidence rating

10. The system of claim 7, wherein the content delivery software module records the number of times a media content is transmitted to the display device.

11. The system of claim 7, wherein the content delivery software module transmits, to a display device, advertising content that is not matched to at least one profile.

12. The display device of claim 7, the display device capable of displaying digital and analog media.

13. The system of claim 7, further comprising a feedback loop software module that produces a promotion code for at least one media content, and records when that promotion code is used.