Marketing optimization system

• US 7,904,327 B2
• Filed: 04/30/2003
• Issued: 03/08/2011
• Est. Priority Date: 04/30/2002
• Status: Active Grant

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Skrzypczak, Michael P., Peo, Carol R., Wells, John C., Pedersen, Ellen, Hackney, Michael L. J., Phelan, William L., Reagen, Jeffrey Q.
• Primary Examiner(s): Weiss; John G
• Assistant Examiner(s): GOLDMAN, MICHAEL H
• Application Number:
  US10/426,596
• Publication Number:
  US 20040093296A1
• Time in Patent Office: 2,869 Days
• Field of Search: 705/14, 705/14.7, 705/14.18, 705/14.1
• US Class Current: 705/7.29
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0216 Investment accounts
• CPC Class Codes: G06Q 30/0274 Split fees
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A marketing optimization module automatically obtaining multi-dimensional marketing data from a market client. The marketing optimization module automatically organizes at least a part of the multi-dimensional marketing data into one or more marketing categories. The marketing optimization module then analyzes all of or a part of the multi-dimensional marketing data to facilitate the optimization of a marketing investment.

Claims

1. A computerized method of optimizing a marketing investment through one or more data processors having processor-implemented instructions, the method comprising:

automatically obtaining, through the processor-implemented instructions, multi-dimensional marketing data from a multi-dimensional database, wherein the multi-dimensional marketing data includes a plurality of data records, and wherein each data record has a value and a plurality of hierarchically-arranged dimensions;

using the multi-dimensional marketing data to define one or more models;

storing the multi-dimensional marketing data in a data staging area including a metadata repository, wherein the metadata repository includes metadata and one or more transformation rules used to transform the multi-dimensional marketing data into multi-dimensional formatted data;

receiving input to use the metadata and at least one transformation rule to transform the multi-dimensional marketing data into multi-dimensional formatted data, wherein the input is received through a graphical interface, and wherein transforming the multi-dimensional marketing data automatically classifies the multi-dimensional marketing data into at least one marketing category; and

receiving a selection corresponding to a marketing investment, wherein the multi-dimensional formatted data is analyzed using the one or more models that correspond to the marketing investment, wherein analyzing produces multi-dimensional forecasted data corresponding to the marketing investment, and wherein the multi-dimensional forecasted data is used to optimize the marketing investment.

2. The method of claim 1, wherein classifying includes apportioning the multi-dimensional marketing data into at least one marketing category.

3. The method of claim 1, wherein classifying includes assigning the multi-dimensional marketing data to at least one marketing category.

4. The method of claim 1, wherein transforming includes aligning the multi-dimensional marketing data with pre-existing multi-dimensional marketing data in at least one marketing category.

5. The method of claim 1, wherein transforming includes integrating the marketing data with pre-existing multi-dimensional marketing data in at least one marketing category.

6. The method of claim 1, wherein marketing categories include marketing goals, financial plans, and technical plans.

7. The method of claim 6, wherein transforming includes linking together at least two marketing goals, financial plans, and technical plans.

8. The method of claim 1, wherein marketing categories include a plans and programs classification, a business results classification, a market factors classification, and an audience and segment classification.

9. The method of claim 1, wherein analyzing includes analyzing effectiveness of a marketing strategy.

10. The method of claim 1, wherein analyzing includes at least one of:

analyzing return on investment, forecasting business results, tracking brand performance, analyzing brand performance, reviewing efficiency of an investment, and measuring a variance of the at least a portion of the multi-dimensional marketing data.

11. The method of claim 10, wherein forecasting business results includes demand forecasting and supply forecasting.

12. The method of claim 10, wherein measuring a variance includes alerting the market client of the variance.

13. The method of claim 1, further comprising:

monitoring a marketing metric of the multi-dimensional marketing data within the at least one marketing category.

14. The method of claim 13, further comprising:

reporting the marketing metric to a market client.

15. The method of claim 1, wherein analyzing includes at least one of:

simulating a response to a marketing strategy to optimize the marketing investment, modeling a market to forecast results of a marketing strategy to optimize the marketing investment, creating an analysis path through the multi-dimensional marketing data optimizing consumer promotions, and annotating results of the analysis.

16. The method of claim 15, wherein modeling a market includes adjusting the marketing model to forecast results of a different marketing strategy to optimize the marketing investment.

17. The method of claim 1, further comprising:

enabling a user to analyze multi-dimensional marketing data in the marketing category to optimize a marketing investment.

18. The method of claim 17, further comprising:

automatically obtaining the user analysis.

19. The method of claim 1, wherein one of the dimensions of the multi-dimensional database is a time-based dimension;

wherein the time-based dimension is arranged in a hierarchy of different time-based levels; and

wherein the hierarchy of different time-based levels comprises different levels of specificity with respect to time.

20. The method of claim 19, wherein the different time-based levels include a month-based level and a quarterly period-based level.

21. The method of claim 19, wherein analyzing includes using an on-line analytical processing (OLAP) system to perform a multi-dimensional analysis on the formatted data.

22. The method of claim 19, wherein another of the dimensions of the multi-dimensional database is a product-based dimension;

wherein the product-based dimension is arranged in a hierarchy of different product-based levels; and

wherein the hierarchy of different product-based levels comprises different levels of specificity with respect to products.

25. The method of claim 1, wherein analyzing includes using one or more algorithms to analyze the formatted data.

23. A system, comprising:

one or more processors;

a computer-readable storage medium containing software instructions executable on the processor to cause the one or more processors to perform operations including;

automatically obtaining multi-dimensional marketing data from a multi-dimensional database, wherein the multi-dimensional marketing data includes a plurality of data records, and wherein each data record has a value and a plurality of hierarchically-arranged dimensions;

using the multi-dimensional marketing data to define one or more models;

storing the multi-dimensional marketing data in a data staging area including a metadata repository, wherein the metadata repository includes metadata and one or more transformation rules used to transform the multi-dimensional marketing data into multi-dimensional formatted data;

receiving input to use the metadata and at least one transformation rule to transform the multi-dimensional marketing data into multi-dimensional formatted data, wherein the input is received through a graphical interface, and wherein transforming the multi-dimensional marketing data automatically classifies the multi-dimensional marketing data into at least one marketing category; and

receiving a selection corresponding to a marketing investment, wherein the multi-dimensional formatted data is analyzed using the one or more models that correspond to the marketing investment, wherein analyzing produces multi-dimensional forecasted data corresponding to the marketing investment, and wherein the multi-dimensional forecasted data is used to optimize the marketing investment

26. The system of claim 23, wherein analyzing includes using one or more algorithms to analyze the formatted data.

24. A computer-readable storage medium encoded with instructions that when executed, cause a computer to perform a marketing optimization method, comprising:

automatically obtaining multi-dimensional marketing data from a multi-dimensional database, wherein the multi-dimensional marketing data includes a plurality of data records, and wherein each data record has a value and a plurality of hierarchically-arranged dimensions;

using the multi-dimensional marketing data to define one or more models;

storing the multi-dimensional marketing data in a data staging area including a metadata repository, wherein the metadata repository includes metadata and one or more transformation rules used to transform the multi-dimensional marketing data into multi-dimensional formatted data;

receiving input to use the metadata and at least one transformation rule to transform the multi-dimensional marketing data into multi-dimensional formatted data, wherein the input is received through a graphical interface, and wherein transforming the multi-dimensional marketing data automatically classifies the multi-dimensional marketing data into at least one marketing category; and

receiving a selection corresponding to a marketing investment, wherein the multi-dimensional formatted data is analyzed using the one or more models that correspond to the marketing investment, wherein analyzing produces multi-dimensional forecasted data corresponding to the marketing investment, and wherein the multi-dimensional forecasted data is used to optimize the marketing investment.

27. The method of claim 24, wherein analyzing includes using one or more algorithms to analyze the formatted data.