You are here:
Home |
Research Services |
Advanced Analytics |
Marketing Mix Modeling
Marketing Mix Modeling
In recent times, we have seen the proliferation of new media
(Internet, viral marketing, event marketing, sports marketing, product
placement, cell phones, etc.), decreased television viewership, the advent of
TiVo and similar technology where viewers can skip through commercials, and
increased cost-cutting pressures. All of this has combined to increase demands
for Marketing Departments to maximize the return on their marketing investment:
that is, to optimize the combination of marketing and advertising investments
in order to generate the greatest sales growth and/or maximize profits.
Marketing mix modeling measures the potential value of all marketing inputs and
identifies marketing investments that are most likely to produce long-term
revenue growth.
Typically, Marketing Mix Modeling involves the use of multiple
regression techniques to help predict the optimal mix of marketing variables.
Regression is based on a number of inputs (or independent variables) and how
these relate to an outcome (or dependent variable) such as sales or profits.
Once the model is built and validated, the input variables (advertising,
promotion, etc.) can be manipulated to determine the net effect on a
company’s sales or profits.
The data that go into creating a Marketing Mix Model include:
-
Economic data
-
Industry data
-
Category data
-
Advertising data (including copy testing)
-
Promotional data
-
Competitive data
-
Service data
-
Product Data
-
Pricing Data
-
Features & Performance
-
Market Outcome Data
Other Advanced Analytic Services include:
Additional Resources from Decision Analyst
If you would like more information on
Advanced Analytics Services,
please contact Dr. John Colias by
email or call 1.800.ANALYSIS (262.5974).
Brochures
Related White Papers
|
