COMPUTER-IMPLEMENTED, AUTOMATED MEDIA PLANNING METHOD AND SYSTEM

• US 20100114650A1
• Filed: 10/31/2008
• Published: 05/06/2010
• Est. Priority Date: 10/31/2008
• Status: Abandoned Application

• Current Assignee: Valassis Communications Incorporated (MX Holdings One LLC)
• Original Assignee: Valassis Communications Incorporated (MX Holdings One LLC)
• Inventors: Clark, Lucy Miller, Westfall, Emily A., Kula, Karen F., Mulvey, Therese, Strnad, Karen, O'Loughlin, Erin E., Kaul, Chris, Donohue, Debra L., Parvar, Alireza Jahan, Curmi, Nancy E., Stewart, Mary Rainer, Worona, Steve, Sherr, Daniel D.
• Application Number:
  US12/262,806
• Publication Number:
  US 20100114650A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• 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

Abstract

An automated computer system for media planning is provided. The automated computer system includes functionality for determining geographically-localized estimated sales data for use in generating media plans. The automated computer system also includes functionality for determining the relative value of a localized geography to a media plan. The automated computer system further includes functionality for a media buyable unit (MBU) score for use in generating a geographically-localized media plan.

Claims

1. An automated computer system for determining geographically-localized estimated sales data for use in generating media plans and comprising a computer having a central processing unit (CPU) for executing machine instructions and a memory for storing machine instructions that are to be executed by the CPU, the machine instructions when executed by the CPU implement the following functions:

receiving sales data from a client for a number of ZIP Codes;

performing lifestyle cluster analysis on the sales data of the client for the number of ZIP Codes to obtain lifestyle cluster data for each of the number of ZIP Codes;

receiving information for a number of carrier routes for each of the number of ZIP Codes;

calculating a lifestyle cluster index for each of the number of ZIP Codes and each of the number of carrier routes for each of the number of ZIP Codes based on the lifestyle cluster data for each of the number of ZIP Codes and the information for the number of carrier routes;

appending household base counts to each of the number of ZIP Codes and each of the number of carrier routes;

calculating actual sales per household for each of the number ZIP Code based on the sales data from the client for the number of ZIP Codes and the household base counts for the number of ZIP Codes; and

calculating estimated total sales per household for each of the number of carrier routes based on the actual sales per household for the ZIP Code associated with the carrier route being considered, the lifestyle cluster index for the carrier route being considered, and the lifestyle cluster index for the ZIP Code associated with the carrier route being considered.

2. The computer system of claim 1, wherein the third calculating function includes calculating estimated total sales per household for each of the number of carrier routes by multiplying the lifestyle cluster index for the carrier route being considered by the ratio of the actual sales per household for the ZIP Code associated with the carrier route being considered to the lifestyle cluster index for the ZIP Code associated with the carrier route being considered.

3. The computer system of claim 2, wherein the machine instructions when executed by the CPU further implement the following function:

calculating estimated total sales for each of the carrier routes based on the estimated total sales per household for the carrier route being considered and the household base count of the carrier route being considered.

4. The computer system of claim 1, wherein the lifestyle cluster data is comprised of a number of lifestyle clusters.

5. The computer system of claim 1, wherein the machine instructions when executed by the CPU further implement the following function:

cleansing the sales data from the client for a number of ZIP Codes against a master ZIP Code file.

6. The computer system of claim 1, wherein the household base counts to each of the number of ZIP Codes or each of the number of carrier routes is the highest base count during a specified date range.

7. An automated computer system for determining a relative value of a localized geography to a media plan and comprising a computer having a central processing unit (CPU) for executing machine instructions and a memory for storing machine instructions that are to be executed by the CPU, the machine instructions when executed by the CPU implement the following functions:

receiving a localized geography and a number of localized geography types;

associating one of the localized geography types to the localized geography to obtain an associated localized geography type;

receiving a functional relationship related to the associated localized geography type;

calculating a geo-score for the localized geography based on the functional relationship; and

calculating the relative value of the localized geography based on the geo-score and a household base count for the localized geography to determine the relative value of the localized geography.

8. The computer system of claim 7, wherein the associated localized geography type is selected from the group consisting of:

trade area, distance from a site, demographic characteristic, demographics/distance, sales, customer behavior, past media promotion responsiveness and custom.

9. The computer system of claim 8, wherein the associated localized geography type is distance from a site and the functional relationship is a distance scaling factor.

10. The computer system of claim 8, wherein the associated localized geography type is demographic characteristic and the functional relationship is a composite demographic index.

11. The computer system of claim 8, wherein the associated localized geography type is sales and the functional relationship is average sales per household.

12. The computer system of claim 8, wherein the localized geography is selected from the group consisting of:

a carrier route, a ZIP Code, an advertising trade zone, a wrap zone or a newspaper zone.

13. An automated computer system for generating a media buyable unit (MBU) score for use in generating a geographically-localized media plan and comprising a computer having a central processing unit (CPU) for executing machine instructions and a memory for storing machine instructions that are to be executed by the CPU, the machine instructions when executed by the CPU implement the following functions:

receiving a geography to be included in a geographically-localized media plan;

receiving information relating to a first and second media product available within the geography;

receiving an activation score for the first media product based on the information relating to the first and second media products, the activation score indicating the value of the first media product relative to the second media product;

receiving a household value score indicative of the value of the geography;

receiving a sell price for the first media product within the geography; and

calculating an MBU score for the first media product based on the activation score, the household value score and the sell price.

14. The computer system of claim 13, the machine instructions when executed by the CPU further implement the following function:

receiving a coverage value for the first media product within the geography, and the calculating function includes calculating the MBU score based on the activation score, the household value score, the coverage value and the sell price.

15. The computer system of claim 13, the machine instructions when executed by the CPU further implement the following functions:

receiving a number of in-home dates for the first media product and a client preferred date for delivery of the first media product and determining an alignment value based on the number of in-home dates and the client preferred dates, and the calculating the MBU score based on the activation score, the household value score, the alignment value and the sell price.

16. The computer system of claim 13, wherein the geography is selected from the group consisting of a carrier route, advertising trade zone or a ZIP Code.

17. The computer system of claim 13, the machine instructions when executed by the CPU further implement the following functions:

receiving a client objective for the geographically-localized media plan and calculating the activation score based on the client objective and the information relating to the first and second media products.

18. The computer system of claim 13, the machine instructions when executed by the CPU further implement the following function:

calculating the household value score based on the geography.

19. The computer system of claim 13, the machine instruction when executed by the CPU further implement the following functions:

receiving a geography type associated with the geography and calculating the household value score based on the geography and geography type.

20. The computer system of claim 13, wherein the household value score is independent of the first or second media products.