Perceptual Mapping EWMBA 206 - University of California

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Transcript Perceptual Mapping EWMBA 206 - University of California

Perceptual Mapping
EWMBA 206
Fall 2007
Professor Ganesh Iyer
Ganesh Iyer
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Perceptual Maps

To gain competitive advantage, a firm must correctly position
itself, its products, or services against competitive offerings.

Need to develop a “Mental Map” of how our product is
perceived by consumers relative to the different competing
products in the marketplace.
» Linking Segmentation and Positioning.

Techniques that help us to construct such mental or Perceptual
Maps are called Multidimensional Scaling and Factor
Analysis.
Ganesh Iyer
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What is a Perceptual Map

A perceptual map is a visual representation of how target
customers view the competing alternatives in a Euclidean space
which represents the market

The map has the following characteristics:
» Pair-wise distances between product alternatives directly indicate
how close or far apart the products are in the minds of customers
» A vector on the map indicates both magnitude and direction in the
Euclidean space. Vectors are usually used to geometrically denote
attributes of the perceptual maps
» The axes of the map are a special set of vectors suggesting the
underlying dimensions that best characterize how customers
differentiate between alternatives
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Perceptual Map of Beer Market
(This slide shows only the products)
•
Old Milwaukee
Budweiser
•
Meister Brau
•
Miller
Beck’s
•
• Heineken
•
•
•
Coors
Stroh’s
• Michelob
•
•
Miller
Lite
•
Coors
Light
Old
Milwaukee Light
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Perceptual Map of Beer Market (cont’d)
(This slide shows only the attributes)
Heavy
Heavy
Full Bodied
Popular
with Men
Special
Occasions
Good Value
Blue Collar
Dining Out
Budget
Premium
Popular
with
Women
Pale Color
On a
Budget
Premium
Light
Light
Less Filling
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Perceptual Map of Beer Market (cont’d)
(This slide shows both products & attributes)
Heavy
Heavy
•
Full Bodied
Old Milwaukee
Budweiser
•
Meister Brau
•
Good Value
Popular
with Men
Miller
•
Beck’s
•
Dining Out
Premium
Coors
Stroh’s
Budget
• Heineken
Special
Occasions
•
Blue Collar
•
Premium
• Michelob
•
On a
Budget
•
Pale Color
Old
Milwaukee Light
Light
Miller
Lite
Light
•
Coors
Light
Popular
with
Women
Less Filling
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Perceptual Mapping Process

Specify the "Relevant" Objects or Products.

Relevance means that the set of products chosen must be the
set of competitive products that are relevant for managerial
decision-making.

Two possible methodologies to collect information on
consumers perception of products:
» Method 1: Attribute based method (Factor Analysis).
» Method 2: Similarity-Based method (Multi-Dimensional Scaling)
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Method 1: Attribute Rating Method
Example: Evaluation of a New Laptop concept.

Select a set of laptop computers of interest to be the target
group including the new concept…(say 4 products)

Decide on the set of relevant attributes on which to capture
consumer perceptions (6 attributes)
» Prior quantitative or qualitative research that elicits important
attributes for the target consumers.

Ensure that consumers are familiar with the laptops that are to
be evaluated (e.g., through video presentation, or actual
prototypes)

Respondents (target customers) evaluate / rank or rate
products.
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Perceptual Mapping
 Data Matrix = 4 (products) X 6 (attributes) X 300 (respondents).
Consumers
A1
A2
A3
A4
P1
P2
P3
P4
Submit data to factor analysis
Interpret the underlying key dimensions (factors) using the directions of the individual attributes
Explore the implications of how consumers’ view the competing products
Data Matrix
Factor Analysis
Perceptual map
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Factor Analysis: Key Concepts

It is difficult to get a clear picture of the market when dealing with so
many attributes and products.

All the data/dimensions might not be necessary to capture consumer
perceptions. Why?

Highly correlated attributes
» Create linear combination of the measures to get a single new dimension of
the original attributes.

Take out attributes on which all computers are rated about the same.

Factor analysis output:
» Say 70% of the information contained in the original attributes can be
represented by creating just 2 new dimensions. These dimensions are
called factors.
» Analysis done using commercial software SPSS or SAS
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Example Plot of Attributes of Laptops on a 2D
Perceptual Map
Common
Easy setup
Slow
 Toshiba 1960CT
Performance
Light
 C
Value
“Butterfly”
Elegant
Look/Styling
The six attributes were measured on semantic differential scales: 1) Slow–Fast operation, 2) Plain–Elegant,
3) Easy–Difficult setup, 4) Poor–Excellent value, 5) Light–Heavy, and 6) Common–Distinctive.
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Example Plot of Attributes of
Laptops on a 2D Perceptual Map
(Plain)
Common
Easy setup
Slow
 Toshiba 1960CT
Performance
 C
“Butterfly”
Good
Value
Light
Elegant
Looks
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Guidelines for Interpreting
Perceptual Maps (Laptop)

The arrow indicates the direction in which that attribute is increasing.

Length of the line from the origin to the arrow is an indicator of the
variance of that attribute explained by the 2D map. The longer this
line, the greater is the importance of that attribute in capturing
variance.

Attribute that are both relatively important (i.e., long vector) and close
to the horizontal (vertical) axis help interpret the meaning of axis.

To represent a laptop on each attribute, draw an imaginary
perpendicular line from the location of the laptop onto that attribute.
(These are shown by dashed lines on the map).

What practical uses can you now put this map to at this stage?
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Limitations

Researcher should be able to clearly conceptualize the
attributes

No perception gap between intended and actual perception of
the attributes.

Works well for hard or functional attributes, (price, product
features).
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Method 2: Overall Similarity Ratings
Multidimensional Scaling

Suppose we are interested in developing a perceptual map of the ED
market consisting of Viagra, Levitra and Cialis.

Suppose we ask a respondent for his perceptions of the similarities
among the 3 products by asking for his judgments about all possible
pairs (3 possible pairs)

Ask the respondent to rank on a scale of 1-7 the similarity of two
products. Do this for all pairs…n products => n(n-1)/2 pairs.
» 1 is very similar
» 7 is very different

How different are the products perceived?
» What are features distinguish different products

Commercial software implementation
» SPSS and SAS.
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ED Market
Viagra Levitra
Viagra
Levitra
Cialis
Cialis
1
1
1
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ED Market
Viagra Levitra
Viagra
Levitra
Cialis
Cialis
1
2
6
1
5.5
1
The numbers are like distances on a perceptual map
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MDS Perceptual Map
5.5
6
2
What more would you like to know?
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Multidimensional Scaling

With 3 products, I can perfectly represent the information in two dimensions

With more products to be represented in two dimensions
»
information loss

Multidimensional scaling (MDS) is a mathematical technique that helps
implement this analysis of similarity perceptions with minimum information loss.

What are advantages/disadvantages of MDS
»
»
»

Allows you to map products and simultaneously infer attributes.
Better for softer attributes which we do not verbalize very well (feel, aesthetics)
Impractical when the number of products are large.
Commercial software implementation
»
SPSS, SAS modules.
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Uses of Perceptual Maps

Customer Analysis and Competitive Analysis
» Understand the competitive market structure as perceived by
customers.
– Position relative to competition
– Select the set of competitors to compete against
» Represent customers’ perceptions in a manner that aids
communication and discussion within the organization

Product
» Perceptions of a new product concept in the context of existing
brands in the market
» Finding the “gap” in the market to position the product.
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Learning

Perceptual maps are about “How our product is perceived by
consumers relative to competition?”
» Link Segmentation and Positioning

Segmentation, Positioning and Perceptual mapping involve
careful and sophisticated quantitative analysis and not
vague managerial intuition.

Two important methods to develop perceptual maps
» Attribute rating
» Similarity rating
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