Systems and methods for optimizing advertising

• US 20050216339A1
• Filed: 01/31/2005
• Published: 09/29/2005
• Est. Priority Date: 02/03/2004
• Status: Abandoned Application

• Current Assignee: In-Store Broadcasting Network LLC (Stingray Group Inc.)
• Original Assignee: In-Store Broadcasting Network LLC (Stingray Group Inc.)
• Inventors: Wolf, Robert, Powell, Robert H., Brazell, Robert
• Application Number:
  US11/047,251
• Publication Number:
  US 20050216339A1
• Time in Patent Office: Days
• US Class Current: 705/14.520
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0254 based on statistics

Abstract

The present invention relates to methods of measuring customer response and methods of optimizing advertising in response to the customer response data. One embodiment of the present invention relates to a method of acquiring data about the advertising preferences of particular groups of customers. For example, this data may include analyzing the shopping response of all married female shoppers over 40 years of age after a particular advertisement is played; this shopping response could then be compared with the shopping response of a similar group after a different advertisement is played. Another embodiment of the present invention relates to optimizing advertising variable settings with respect to acquired advertising data in an effort to identify optimized advertising variable settings for identifiable groups of customers. Yet another embodiment of the present invention relates to a method of generating an advertisement with optimized advertisement variable settings for an advertising target group. For example, if data indicates that a particular demographic responds to a male advertiser, the advertisement will be spoken with a male voice and played during that time period. Yet another embodiment of the present invention relates to measuring customer response data of various message media and combinations of message media.

Claims

1. A method for obtaining metric media values comprising the steps of:

broadcasting a test advertisement via at least one form of media within a restricted environment;

obtaining customer response data in response to the broadcasted test advertisement before each corresponding customer leaves the restricted environment; and

generating metric values from the customer response data for the at least one form of media.

2. The method of claim 1, wherein the at least one form of media includes any single or combination of media.

3. The method of claim 1, wherein the restricted environment is a retail store.

4. The method of claim 1, wherein the at least one form of media includes audio, video, radio, television, billboard, taste, and smell.

5. The method of claim 1, wherein the step of obtaining customer response data in response to the broadcasted test advertisement further includes obtaining customer response data from at least one customer response device.

6. The method of claim 1, wherein the step of obtaining customer response data in response to the broadcasted message further includes obtaining out-of-store customer response data from an advertiser for use in generating combination metrics of in-store media and out-of-store media.

7. The method of claim 1 further including the step of correlating the customer response data and generated metric values with particular customer information.

8. The method of claim 7, wherein the step of correlating the customer response data and generated metric values with particular customer information further includes obtaining customer information from a customer information device.

9. A method for predicting the most effective combination of media comprising the steps of:

broadcasting a plurality of test advertisements via a plurality of media permutations;

obtaining customer response data in response to the test advertisements;

generating metric values from the customer response data for the plurality of media permutations;

graphing the metric values of each media permutation in a curve illustrating the metric value versus the allocated cost for broadcasting in each media permutation.

10. The method of claim 9, wherein the plurality of media permutations includes combinations of video, audio, visual, taste, and smell.

11. The method of claim 9, wherein the plurality of media permutations includes combinations of in-store media and out-of-store media.

12. The method of claim 9, wherein the allocated cost for broadcasting in each media permutation is the cost per rating point.

13. The method of claim 9 further including identifying an inflection point on each graph to identify the most efficient metric response for a particular media permutation.

14. A method for obtaining metric in-store media values comprising the steps of:

broadcasting a test advertisement in a store environment via a plurality of media;

obtaining customer response data in response to the broadcasted test advertisement; and

generating metric values from the customer response data for the plurality of in-store media.

15. The method of claim 14, wherein the plurality of in-store media includes any combination of in-store media.

16. The method of claim 14, wherein the plurality of media includes combinations of audio, video, radio, television, billboard, taste, and smell.

17. The method of claim 14, wherein the step of obtaining customer response data in response to the broadcasted test advertisement further includes obtaining customer response data from at least one customer response device.

18. The method of claim 14 further including the step of correlating the customer response data and generated metric values with particular customer information.

19. The method of claim 18, wherein the step of correlating the customer response data and generated metric values with particular customer information further includes obtaining customer information from a customer information device.

20. The method of claim 14, wherein the step of generating metric values from the customer response data for the plurality of in-store media utilizes a process of personal probability.

21. The method of claim 14, wherein the step of generating metric values from the customer response data for the plurality of in-store media utilizes a process of random duplication.