PHASE 4: GROUP PROJECT SUBMISSION BOARD
KENNETH C HOLMES
MGMT600-1502A-01
PROFESSOR HENRIETTA OKORO
MAY 11, 2015
MULTIVARIATE TECHNIQUES AND THEIR USE IN BUSINESS
Introduction:
WidgeCorp management was contacted by a market research firm, and proposed the
purchase of a business. I have been charged with researching Multivariate techniques including:
Factor Analysis, Multidimensional Analysis, and Cluster Analysis, and research how the three
techniques are used in business. The following research conveys the results.
Factor Analysis:
Factory Analysis is simply changing one variable to see the effect, if any on the outcome.
Factor Analysis has two types: explanatory factor analysis where the factors are determined by
the data; and confirmatory factor analysis which is used to test and confirm hypotheses in
structural equation modeling (N.A., Factor Analysis in Market Research, 2015). The process
requires one factor at a time be changed to determine the variable and outcome correlation. This
rule is essential because there may be many factors, and changing one variable may increase or
decrease the other variable. For example: changing a feature of a product can significantly
increase or decrease the demand (sales) for that product. Variables can include: product features,
packaging, product size, product color, the taste, the price, where to purchase the product,
product advertising, level of service, and product quality (Lorette, 2015).
Factor Analysis helps companies determine which marketing efforts to pursue, which
need further evaluation, and which to eliminate. The mission of FA is to design the perfect
product for the customer to increase sales. The testing is usually done with focus groups and
surveys where they are shown several versions of a product, then choose which version they like
best, and explain why, enabling the manufacturer to gather information from customers without
making costly changes to the product. This step also enables the manufacturer to see the product
from the customer’s perspective, determine the most important factors to the customer, and make
changes to the product that will attract more customers including: improved flavor, more flavor
choices, more color choices, improved features, improved performance, etc., in order to increase
sales. The process also enables the manufacturer to compare the sales before and after the
changes, and properly conclude through Factor Analysis the changes made are important to their
customer base. Factor Analysis is not a science, because large scale testing is commonly applied
to determine the relationship of the variables. For that reason it is best to have an outside market
research expert conduct the Factor Analysis and evaluate the results to ensure accurate cause and
effect relationships (Lorette, 2015).
Real companies that used Factor Analysis:
Wal-Mart used Factor Analysis to address a series of issues they faced in 2006, to bounce
back and become the nation’s low price leader. Those issues include: being condemned for cheap
business practices including low pay and cheap health care benefits; exporting jobs and
destroying small business; litigation and a class action discrimination suit; internal fraud and tax
evasion on the top level; and bad press from a from a Robert Greenwald film titled “Wal-Mart:
The High Cost of Low Prices” (Walmart Stores Inc., 2008).
Multidimensional Scaling:
Multidimensional Scaling (MDS) is a statistical techniques commonly used in business
marketing and social science, and is used to ascertain consumer attitudes and preferences about
product similarities. Respondents evaluate the similarities between products, and compare them
to what they see as the perfect product, then their responses are charted on a perceptual map (a
grid with both X and Y axes), where the X and Y axes represent a specific product aspect (N.A.,
Multidimensional Scaling, 2015). Analysis of the perpetual map helps the manufacturer create
the perfect product based on what features are important to the respondent. MDS advantages
include: the researcher provides no judgements; respondents are no presented preset attributes;
and the respondent’s judgement provides the product factors (N.A., Multidimensional Scaling in
Marketing, 2015).
Steps in Multidimensional Scaling (N.A., Multidimensional Scaling in Marketing, 2015):
1. Formulate the problem: what brand names are we comparing?; how many brand names
should we compare?; what is the purpose of the study?
2. Gather input data: from the questions asked the respondents.
3. Run the MDS statistical program: Using either Metric or Nonmetric MDS.
4. Chart the results and determine the dimensions.
5. Test the results for reliability and validity.
Real companies that used Multidimensional Scaling:
Sam’s club used MDS to determine the neurological preferences of their logo candidates,
and selected their “simple steps to saving green” logo campaign, which identifies products in
their stores that are environmentally friendly based on: the way they are created, processed, and
distributed. These products have been certified by outside organizations that set environmental
protection standards and include: compact laundry detergent, farmed products, seafood products,
energy efficient appliances, organic foods, sustainably produced wood products, water efficient
toilets and shower heads, and reduced carbon emission products (N.A., Sam's Club: A Case
Study on Logo Evaluation, 2000).
Cluster Analysis:
Cluster Analysis is an explanatory data analysis tool that takes similar observations from
a larger population and breaks them into smaller groups based on maximal or minimal
correlation. Cluster Analysis has many features including: the ability to find concealed patterns
and structures in data without a specific assumption; the ability to identify similarities in specific
behaviors or parameters; and the ability to reveal patterns in data without explaining why they
are there. There are two types of Cluster Analysis including: non-hierarchical which divides
larger datasets into smaller data sets; and hierarchical which pairs the clusters in a hierarchical
manner, like a pyramid. Which type used is based on the objective of clustering, the type of
output desired, the hardware and software facilities available, and the size of the dataset.
Clustering is used for several reasons including: performing segmentation from a larger group of
data. For example, clustering similar products based on their attributes; anomaly detection. For
example, identifying fraudulent transactions; and breaking large data sets into smaller groups for
use with other testing techniques. (Vohra, 2011).
Real companies that used Cluster Analysis:
SABMiller, a leading international beer brewers and producer of Coca Cola products
used Cluster Analysis to: classify their liquids to make communication easier for both marketing
and technical staff; help consumers understand the specific differences between beers; determine
consumer preferences; identify opportunities for their brands, and to determine the acceptability
of their brands in local and international markets (Camo, 2015).
REFERENCES
Camo. (2015). SABMiller: Bringing science to the art of brewing better beers . Retrieved from
Case Studies: Multivariate Data Analysis-Camo: www.camo.com/resources/casestudies.html
Lorette, K. (2015). Importance of Factor Analysis in Marketing. Retrieved from
smallbusiness.chron.com › … › Importance of Marketing
N.A. (2000). Sam's Club: A Case Study on Logo Evaluation. Retrieved from Sam's Club Case
Study Logo: Logo Evaluation-Sands Research:
www.sandsresearch.com/Sam's_Case_Study.aspx
N.A. (2015). Factor Analysis in Market Research. Retrieved from
https://www.b2binternational.com/.../factor-analysis
N.A. (2015). Multidimensional Scaling. Retrieved from
www.allbusiness.com/barrons_dictionary/dictionary-multidimensional...
N.A. (2015, May 3). Multidimensional Scaling in Marketing. Retrieved from Econonomic
Expert.com: www.economicexpert.com/a/Multi:dimensional:scaling:in:marketing.htm
Vohra, G. (2011, February 23). Cluster Analysis for Business. Retrieved from ezinearticles.com ›
Business
Walmart Stores Inc. (2008, March 24). Wal-Mart Stores, Inc. Case Study by Rao. Retrieved from
www.academon.com › Case Study