Marketing Data Analysis

Rian BEISE-ZEE

From Marketing Metrics, 2nd Ed. by Paul W. Farris, et. al.

(ISBN: 0321750403) Copyright © 2012 Pearson Education, Inc. All rights reserved.

Perceptual Mapping

Positioning

… is establishing a specific customer perception about an existing product or brand.

Positioning

• Happens in the mind of the customers.

• We can position the same product differently.

• Defined relative to competitors, therefore can

keep a product/service “different” from competitors

products in the mind of the customer even if it is

physically the same

Positioning Principles

Same Product - Different Perception

Mouthwash

Perceptual Mapping

(or: Multidimensional Scaling)

• We can think of a variety of product attributes that possibly differentiate a product; however, consumers are unlikely to keep many attributes in mind.

• We can position a brand, but we don’t know if consumers are really “buying it”.

1. Perceptual mapping is a tool to measure what dimensions consumers use to differentiate products.

2. For marketers two or three dimensions allow a graphic representation, which makes strategy building a lot easier (but it does not mean that the world is really that simple).

Perceptual Map

The outcome of a multidimensional scale is

called ‘perceptual map’, a visual representation

which helps to derive strategic conclusions

about:

• What main dimensions are used by consumers to compare

Brands? (but not its importance!)

• Who are our competitors and how similar are they to our

Brand?

• What product clusters do consumers perceive?

• Are there holes in the market that are not yet covered?

Example: Detergent

Methods

• There are several methods

– Attribute-based: we start with many attributes and

try to reduce them to 2 or 3 main dimensions (by

means of factor analysis or discriminant analysis)

– Comparison-based: We start with comparisons

between two brands and end up with interpreting a

distance field

Attribute based MDS

1 2 3 4 5

Heavy

Action

Good Value

Budget

Relaxation

Popular with women

Sporty

Popular with men

Premium

Special Occasion

Sex Appeal

Rate each beer brand‘s association

Not

descriptive

at all

Totally

descriptive

From Moore and Pessemier (1993).

Comparison-based MDS

Beer Chang vs. Singha Beer

Totally Extremely

similar dissimilar

--- --- --- --- --- --- ---

1 2 3 4 5 6 7

Expl: Similarity ratings of 4 Objects

(for example products or companies)

A B C D

A

B 3.2

C 1.7 3.9

D 5.1 3.3 4.7

A Two Dimensional Solution of Empirical

Distances

Dimensionality

• How many dimensions a perceptual map has depends on the complexity of the similarity data. Often, two dimensions are sufficient. More than three are difficult to interpret. But one dimension is also quite possible.

• Two dimensions are often selected because it looks better.

• The correct method to decide on the number of dimensions is the stress value and the scree plot.

Labeling the axes

(= interpreting the dimensions)

• MDS only delivers the map but no clue about how to

interpret the dimensions

• Based on individual judgment of the researcher, e.g.

by

– known objective attributes

– Based on additional questions on the Brands’ attributes

• Based on objective vector algorithms with additional

attribute information

Interpreting the Dimensions:

Soft Drinks Example

Perceptual Map for Beer in Thailand

Interpreting the Dimensions

Problems with MDS

• Different methods lead to different maps (use several and analyze the differences)

• Different consumer groups have different perceptual maps (e.g. users/non-users) but MDS assumes homogeneity

• Different users consider different attributes and attach different importance to attributes

• Less than 4 objects per dimensions lead to misleading solutions but a large number of comparisons often overexert respondents.

Correspondence Analysis

• Another method to derive a perceptual map

based on the relationship between objects

(brands, products) and nominal attributes

(gender, age group, lifestyle)

• A perceptual map can be derived from any

cross-tabulation (frequency count)

Expl. Cross-tabulation

Product Sales

A B C Total Young adults (>35)

20 20 20 60

Middle age (36-55)

40 10 40 90

Mature (55+)

20 10 40 70

Total

80 40 100 220

Process of Correspondence Analysis

• Expected cell count under independence = (column total/total * Row total/total)*total

• Chi-quare value for each cell = actual cell count – expected cell count

expected cell count

• Chi-sqare is used as a measure of association

(similarity) between row and column :

– The greater chi-square the higher the similarity

– The more negative the higher the dissimilarity

Derived Perceptual Map

The Ford Ka

Which of these cars is more similar to the

Ford Ka?

VW Polo

VW Polo Ad

VW Polo Ad

Renault Twingo Ads

Toyota Rav4

Fiat 500 (Cinquecento)

Opel Tigra

One Dimension Solution of all Respondents

Object Points

Common Space

Dimension 1

1.51.0.50.0-.5-1.0

FIAT500 MICRA P106POLO FIESTACORSA TWINGO RAV4 KA TIGRA

Two dimension solution of all respondents

Object Points

Common Space

Dimension 1

1.51.0.50.0-.5-1.0

Dim

en

sio

n 2

.6

.4

.2

-.0

-.2

-.4

-.6

FIAT500

MICRA

P106

POLO

FIESTA

CORSA

TWINGO

RAV4

KA

TIGRA

Solution for Respondents with Ka

Preference

Object Points

Common Space

Dimension 1

1.51.0.50.0-.5-1.0

Dim

en

sio

n 2

.6

.4

.2

0.0

-.2

-.4FIAT500

MICRA

P106

POLO

FIESTA

CORSA

TWINGO

RAV4

KA

TIGRA

Solution for Respondents with low Ka-liking

Object Points

Common Space

Dimension 1

1.51.0.50.0-.5-1.0

Dim

en

sio

n 2

.8

.6

.4

.2

-.0

-.2

-.4

-.6

FIAT500MICRA

P106POLO

FIESTA

CORSA

TWINGO

RAV4

KA

TIGRA