Brand Health Measurement - Investment Optimization Model

• US 20140019178A1
• Filed: 07/12/2012
• Published: 01/16/2014
• Est. Priority Date: 07/12/2012
• Status: Abandoned Application

• Current Assignee: Dell Products LP (Dell Technologies Inc.)
• Original Assignee: Yingchi Chen
• Inventors: Narang, Rajiv, Kortum, Natalie, Chen, YingChi, Sadler, George, Vaughn, Brandon
• Application Number:
  US13/547,322
• Publication Number:
  US 20140019178A1
• Time in Patent Office: Days
• US Class Current: 705/7.11
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A system and method are disclosed for optimizing brand equity return on investment (ROI). Original input data associated with a plurality of brand equity variables is processed using a brand equity ROI model to generate a first brand equity value, which in turn is processed to generate a dependent variable. Input data corresponding to an individual brand equity variable is then processed to generate changed input data, which in turn is processed by the brand equity ROI model with the original input data and the dependent variable to generate a second brand equity value. The first and second brand equity values are then processed to determine the effect of the changed data on the first brand equity value.

Claims

1. A computer-implementable method for optimizing brand equity return on investment (ROI), comprising:

receiving original input data associated with a plurality of brand equity variables;

processing the original input data to generate a first brand equity value, the input data processed by a brand equity ROI model;

processing the first brand equity value to generate a dependent variable;

changing input data corresponding to an individual brand equity variable of the plurality of brand equity variables to generate changed input data;

using the brand equity ROI model to process the original input data, the dependent variable, and the changed input data with to generate a second brand equity value; and

processing the first and second brand equity values to determine the effect of the changed data on the first brand equity value.

2. The method of claim 1, wherein the original input data comprises measurement data associated with at least one of:

a product;

customer service;

sales;

corporate reputation;

supply;

marketing communications;

competition;

pricing; and

externalities.

3. The method of claim 1, wherein an analytic method used by the brand equity ROI model comprises at least one of:

multivariate analysis;

regression analysis;

Bayesian modeling;

structural equation modeling (SEM); and

business intelligence analytics.

4. The method of claim 1, wherein the original input data is cleansed prior to being processed.

5. The method of claim 1, wherein:

the original input data comprises time series data further comprising lag values; and

the lag values are processed to solve the lag values prior to being processed.

6. The method of claim 1, wherein the brand equity ROI model is pruned prior to being processed to ensure business sense.

7. A system comprising:

a processor;

a data bus coupled to the processor; and

a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for;

receiving original input data associated with a plurality of brand equity variables;

processing the original input data to generate a first brand equity value, the input data processed by a brand equity ROI model;

processing the first brand equity value to generate a dependent variable;

changing input data corresponding to an individual brand equity variable of the plurality of brand equity variables to generate changed input data;

using the brand equity ROI model to process the original input data, the dependent variable, and the changed input data with to generate a second brand equity value; and

processing the first and second brand equity values to determine the 22 effect of the changed data on the first brand equity value.

8. The system of claim 7, wherein the original input data comprises measurement data associated with at least one of.

a product;

customer service;

sales;

corporate reputation;

supply;

marketing communications;

competition;

pricing; and

externalities.

9. The system of claim 7, wherein an analytic method used by the brand equity ROI model comprises at least one of:

multivariate analysis;

regression analysis;

Bayesian modeling;

structural equation modeling (SEM); and

business intelligence analytics.

10. The system of claim 7, wherein the original input data is cleansed prior to being processed.

11. The system of claim 7, wherein:

the original input data comprises time series data further comprising lag values; and

the lag values are processed to solve the lag values prior to being processed.

12. The system of claim 7, wherein the brand equity ROI model is pruned prior to being processed to ensure business sense.

13. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:

receiving original input data associated with a plurality of brand equity variables;

processing the original input data to generate a first brand equity value, the input data processed by a brand equity ROI model;

processing the first brand equity value to generate a dependent variable;

changing input data corresponding to an individual brand equity variable of the plurality of brand equity variables to generate changed input data;

using the brand equity ROI model to process the original input data, the dependent variable, and the changed input data with to generate a second brand equity value; and

processing the first and second brand equity values to determine the effect of the changed data on the first brand equity value.

14. The non-transitory, computer-readable storage medium of claim 13, wherein the original input data comprises measurement data associated with at least one of:

a product;

customer service;

sales;

corporate reputation;

supply;

marketing communications;

competition;

pricing; and

externalities.

15. The non-transitory, computer-readable storage medium of claim 13, wherein an analytic method used by the brand equity ROI model comprises at least one of:

multivariate analysis;

regression analysis;

Bayesian modeling;

structural equation modeling (SEM); and

business intelligence analytics.

16. The non-transitory, computer-readable storage medium of claim 13, wherein the original input data is cleansed prior to being processed.

17. The non-transitory, computer-readable storage medium of claim 13, wherein:

the original input data comprises time series data further comprising lag values; and

the lag values are processed to solve the lag values prior to being processed.

18. The non-transitory, computer-readable storage medium of claim 13, wherein the brand equity ROI model is pruned prior to being processed to ensure business sense.