Method of estimating expected revenues from business directory books

• US 20020165756A1
• Filed: 03/02/2001
• Published: 11/07/2002
• Est. Priority Date: 03/02/2001
• Status: Active Grant

• Current Assignee: Verizon Patent and Licensing Incorporated (Verizon Communications Inc.)
• Original Assignee: Verizon Laboratories Incorporated (Verizon Communications Inc.)
• Inventors: Cermak, Gregory W., Tobin, Roger L.
• Granted Patent: US 7,039,598 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: G06Q 30/0247 Calculate past, present or future revenues
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0267 Wireless devices
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

A new system of analyzing advertising revenue derivation is provided that is particularly useful for predicting an amount of revenue that can be expected from advertisements placed in a business directory book having a certain geographic coverage. The system comprises estimating a preference factor of advertisers located in a first geographic area of placing advertisements in other geographic areas. This preference factor, along with other demographic data, is used to calculate a choice probability that advertisers will choose to place an advertisement in one business directory book over other competing books. A total amount of expected revenue for each particular geographic area within a metropolitan area is calculated. Finally, the total amount of expected revenue attributable to a particular business directory book is predicted based on the choice probability and the total amount of expected revenue for each geographic area.

Claims

1. A method of analyzing geographic advertising preferences of potential advertisers, comprising the step:

determining a numerical preference factor indicative of a relative preference of the potential advertisers located in a first geographic area of placing advertisements in a second geographic area.

2. The method of claim 1, wherein said numerical preference factor is calculated based on the relative distance between said first geographic area and said second geographic area.

3. The method of claim 1, wherein said numerical preference factor includes aggregate income of households located in said second geographic area.

4. The method of claim 1, wherein said numerical preference factor includes total sales of non-manufacturing businesses located in said second geographic area.

5. The method of claim 1, wherein said numerical preference factor is determined using:

(i) the relative distance between said first geographic area and said second geographic area;

(ii) an aggregate income of households located in said second geographic area; and

(iii) a total sales of non-manufacturing businesses located in said second geographic area.

6. The method of claim 5, wherein said numerical preference factor is calculated according to the following equation:

P_ji=β

_o+β

_Dln(D)+β

_II+β

_BB

where P_ji is said numerical preference factor;

D is said relative distance between said first geographic area and said second geographic area;

I is said aggregate income of households located in said second geographic area;

B is said total sales of non-manufacturing businesses located in said second geographic area; and

β

₀, β

_D, β

_I, and β

_B are estimated constants.

7. A method of predicting advertising revenue derived from a business directory book, comprising the steps of:

estimating a geographic preference of advertisers located in a first geographic area of placing advertisements in a second geographic area; and

determining an expected amount of advertising revenue attributable to the business directory book based on said geographic preference.

8. The method of claim 7, further comprising the steps of:

determining a choice probability factor indicative of the probability that advertisers located in said first geographic area will choose to advertise in the business directory book; and

deriving an expected total amount of advertising revenue from said first geographic area.

9. The method of claim 8, wherein said step of deriving an expected total amount of advertising revenue includes a total number of non-manufacturing businesses located in said first geographic area and a total amount of sales made by said non-manufacturing businesses.

10. The method of claim 8, wherein said step of determining a choice probability factor includes said geographic preference.

11. The method of claim 10, wherein said step of determining a choice probability factor includes an aggregate income of households to which the business directory book is distributed and upon whether a local telephone carrier publishes a competing business directory book.

12. The method of claim 8, further comprising the step of determining a predicted advertising revenue derived from the business directory book based on said choice probability factor and said expected total amount of advertising revenue from said first geographic area.

13. The method of claim 7, wherein said numerical preference factor is determined using the relative distance between said first geographic area and said second geographic area.

14. The method of claim 7, wherein said numerical preference factor is determined using an aggregate income of households located in said second geographic area.

15. The method of claim 7, wherein said numerical preference factor is determined using a total sales of non-manufacturing businesses located in said second geographic area.

16. The method of claim 7, wherein said numerical preference factor is determined using:

(i) the relative distance between said first geographic area and said second geographic area;

(ii) an aggregate income of households located in said second geographic area; and

(iii) a total sales of non-manufacturing businesses located in said second geographic area.

18. The method of claim 17, further comprising the steps:

repeating said estimating, determining, deriving, and calculating steps for a plurality of subdivided geographic areas located within a larger geographic area; and

summing said expected amount of advertising revenue attributable to the business directory book from each of said subdivided geographic areas.

20. The system of claim 19, wherein said cell preference model is responsive to a physical distance between said first and second cells.

21. The system of claim 20, wherein said cell preference model is further responsive to an income level of households located in said second cell.

22. The system of claim 21, wherein said revenue model is responsive to characteristics of said first and second cells.

23. The system of claim 22, wherein said characteristics comprise an amount of sales derived by businesses located in said first and second cells.

24. The system of claim 23, further comprising an output value indicative of a total amount of revenue that can be expected to be derived from a particular business directory book derived from said probability and said total advertising revenues potential.

17. A method of predicting advertising revenue derived from a business directory book, comprising the steps of:

estimating a geographic preference of advertisers located in a first geographic area of placing advertisements in a second geographic area;

determining a choice probability factor indicative of a probability that advertisers located in said first geographic area will choose to advertise in the business directory book based on said geographic preference;

deriving an expected total amount of advertising revenue from said first geographic area; and

calculating an expected amount of advertising revenue attributable to the business directory book based on said choice probability factor and said expected total amount of advertising revenue from said first geographic area.

19. A system for evaluating expected revenues derived from business directory books, comprising:

a cell preference model that determines a value indicative of the preference of advertisers located in a first cell to advertise in a second cell;

a book choice model responsive to said advertiser preference that determines a probability that an advertiser located in said first cell will choose to advertise in a business directory book having certain characteristics; and

a revenue model that estimates total advertising revenue potentials respectively of said first and second cells.