System and method for determining the effectiveness and efficiency of advertising media

• US 6,772,129 B2
• Filed: 09/04/2002
• Issued: 08/03/2004
• Est. Priority Date: 09/04/2001
• Status: Expired due to Term

• Current Assignee: Planning Power Services Incorporated, Power Planning Service, Inc.
• Original Assignee: Planning Power Service, Inc.
• Inventors: Alvarez, Alan P., Rice, Sean C.
• Primary Examiner(s): MEINECKE DIAZ, SUSANNA M
• Application Number:
  US10/234,361
• Publication Number:
  US 20030078832A1
• Time in Patent Office: 699 Days
• Field of Search: 705/10, 705/14
• US Class Current: 705/14.41
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0272 Period of advertisement exposure

Abstract

A method for determining the relationship between historical media support levels, media cost or spending, product pricing and product sales that provides the relative effectiveness and efficiency of a specific form of media at both a macro and micro level, as well as an understanding of media half-life and media saturation points. This method measures all known forms of media such as the commonly used media of television, radio and newspaper, as well as new forms of media advertising such as internet banners and email along with lesser used media like sides of buildings and taxi tops.

Claims

1. A method for determining the effect of an advertisement on profits generated by sales of a product advertised in a given market area over a particular period of time, the method comprising utilizing a computing device to perform the steps of:

compiling a total of the number of impressions an advertisement makes on a plurality of potential customers through at least one specific form of advertising;

establishing at least one reduction rate for each of the total number of impressions for the at least one specific form of advertising;

correlating the at least one reduction rate for the at least one specific form of advertising with product sales;

determining at least one correlation variable for the at least one specific form of advertising;

calculating at least one saturation curve variable for the at least one specific form of advertising;

correlating the at least one saturation curve variable with product sales;

determining a first regression coefficient for the at least one specific form of advertising;

determining a second regression coefficient for the at least one specific form of advertising;

averaging the first and second regression coefficients for the at least one specific form of advertising to obtain an average coefficient for the at least one specific form of advertising; and

calculating the product sales per impression using the average coefficient for the at least one specific form of advertising.

2. The method of claim 1 wherein:

the compiling step is comprised of compiling a total number of impressions that an advertisement makes on a plurality of potential customers for each specific form of advertising in a series of specific forms of advertising;

the establishing step is comprised of establishing a series of reduction rates for each of the total number of impressions for each specific form of advertising in a series of specific forms of advertising;

the series of reduction rates are correlated with product sales;

the step of calculating at least one saturation curve variable is comprised of calculating a series of saturation curve variables for each of a series of specific forms of advertising;

the correlating step is comprised of correlating the series of saturation curve variables for each of a series of specific forms of advertising with product sales;

determining the first regression coefficient is comprised of determining the first regression coefficient for each specific form of advertising by identifying a highest correlation saturation curve variable in the series of saturation curve variables for each of a series of specific forms of advertising and regressing the highest correlation saturation variable curve for each specific form of advertising versus product sales; and

determining the second regression coefficient is comprised of regressing, in one regression, the highest correlation saturation curve for each specific form of advertising versus product sales.

3. The method of claim 1 further comprising calculating the product sales per dollar spent for each specific form of advertising.

4. The method of claim 1 wherein the at least one correlation variable is determined by correlating the at least one reduction rate versus product sales.

5. The method of claim 1 wherein the at least one saturation curve variable is calculated by transforming at least one correlation variable with at least one saturation curve transformation.

6. The method of claim 5 wherein the at least one correlation variable is the highest correlation variable.

7. The method of claim 1 wherein the first regression coefficient is determined by performing a first regression analysis on the at least one saturation curve variable for the at least one specific form of advertising.

8. The method of claim 7 wherein the first regression analysis is performed using an ordinary least squares regression technique.

9. The method of claim 1 wherein an overall highest correlation curve is the total of the highest of the at least one correlation curve for each specific form of advertising.

10. The method of claim 1 wherein the second regression coefficient is determined by performing a second regression analysis on an overall highest saturation curve versus product sales.

11. The method of claim 1 wherein the at least one specific form of advertising is comprised of the group comprised of television, radio and print media.

12. A data processing system for determining the effect of an advertisement on profits generated by sales of a product advertised in a given market area over a particular period of time, the data processing system comprising an effectiveness and efficiency calculation component in a processor that calculates a total of the number of impressions the advertisement makes on a plurality of potential customers through at least one specific form of advertising, establishes a reduction rate for each of the total number of impressions for the at least one specific form of advertising, determines at least one correlation variable for the at least one specific form of advertising, calculates at least one saturation curve variable for the at least one specific form of advertising, correlates the at least one saturation curve variable with product sales, determines a first regression coefficient for the at least one specific form of advertising, calculates an overall highest correlation curve, determines a second regression coefficient, averages the first and second regression coefficients for each specific form of advertising to obtain an average coefficient for each specific form of advertising, and calculates the product sales per impression using the average coefficient for each specific form of advertising;

and

an output device that outputs the product sales per impression to a user such that the user can employ the product sales per impression to allocate advertising funds.

13. The data processing system of claim 12 wherein the output device is a monitor that displays the calculated total number of product sales resulting from the advertising impression.

14. The data processing system of claim 12 wherein the output device is a printer that generates a print-out of the calculated total number of product sales resulting from the advertising impression.

15. The data processing system of claim 12 wherein the effectiveness and efficiency component calculates in the processor the product sales per dollar spent for each specific form of advertising.

16. A computer-readable medium having computer-executable instructions for performing a method comprising:

compiling a total number of impressions an advertisement makes on a plurality of potential customers through at least one specific form of advertising;

establishing a reduction rate for each of the total number of impressions for the at least one specific form of advertising;

determining at least one correlation variable for the at least one specific form of advertising;

calculating at least one saturation curve variable for the at least one specific form of advertising;

correlating the at least one saturation curve variable with product sales;

determining a first regression coefficient for the at least one specific form of advertising;

determining a second regression coefficient;

averaging the first and second regression coefficients for each specific form of advertising to obtain an average coefficient for each specific form of advertising; and

calculating the product sales per impression using the average coefficient for each specific form of advertising.

17. The computer-readable medium of claim 16 wherein

the compiling step is comprised of compiling a total number of impressions that an advertisement makes on a plurality of potential customers for each specific form of advertising in a series of specific forms of advertising;

the establishing step is comprised of establishing a series of reduction rates for each of the total number of impressions for each specific form of advertising in a series of specific forms of advertising;

the series of reduction rates are correlated with product sales;

the step of calculating at least one saturation curve variable is comprised of calculating a series of saturation curve variables for each of a series of specific forms of advertising;

the correlating step is comprised of correlating the series of saturation curve variables for each of a series of specific forms of advertising with product sales;

determining the first regression coefficient is comprised of determining the first regression coefficient for each specific form of advertising by identifying a highest correlation saturation curve variable in the series of saturation curve variables for each of a series of specific forms of advertising and regressing the highest correlation saturation variable curve for each specific form of advertising versus product sales; and

determining the second regression coefficient is comprised of regressing, in one regression, the highest correlation saturation curve for each specific form of advertising versus product sales.

18. The computer-readable medium of claim 16 wherein the at least one correlation variable is determined by correlating the at least one reduction rate versus product sales.

19. The computer-readable medium of claim 16 wherein the at least one saturation curve variable is calculated by transforming at least one correlation variable with at least one saturation curve transformation.

20. The computer-readable medium of claim 19 wherein the at least one correlation variable is the highest correlation variable.

21. The computer-readable medium of claim 19 wherein the first regression coefficient is determined by performing a first regression analysis on the at least one saturation curve variable for the at least one specific form of advertising.

22. The computer-readable medium of claim 21 wherein the first regression analysis is performed using an ordinary least squares regression technique.

23. The computer-readable medium of claim 16 wherein the overall highest correlation curve is the total of the highest of the at least one correlation curve for each specific form of advertising.

24. The computer-readable medium of claim 16 wherein the second regression coefficient is determined by performing a second regression analysis on the overall highest saturation curve versus product sales.

25. The computer-readable medium of claim 16 wherein the at least one specific form of advertising is comprised of the group comprised of television, radio and print media.