GroupC-Perceptual Mapping- Attribute Based

GroupC-Perceptual Mapping- Attribute Based

Perceptual Mapping

A perceptual map is a visual representation of how people view the competing alternatives in a Euclidean space which represents the market. It can be used to plot the interrelationships of consumer products, industrial goods, institutions, as well as populations. Virtually any subjects that can be rated on a range of attributes can be mapped to show their relative positions in relation both to other subjects as well as to the evaluative attributes Compared to other data mining and data analysis techniques Perceptual Mapping is growing increasingly popular because its mathematical basis is easier to understand and its results are easier to interpret.

The map has the following characteristics:

1.      Pair-wise distances between product alternatives directly indicate how close or far apart the products are in the minds of customers

2.      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

3.      The axes of the map are a special set of vectors suggesting the underlying dimensions that best characterize how customers differentiate between alternatives

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 consumer’s perception of products:

1.      Method 1: Attribute based method (Factor Analysis).

2.      Method 2: Similarity-Based method (Multi-Dimensional Scaling)

Attribute Rating Method

Example: Evaluation of a Store Satisfaction Level

1.      Select a set of Stores of interest to be the target group (say 4 products)

2.      Decide on the set of relevant attributes on which to capture consumer perceptions (6 attributes)

3.      Prior quantitative or qualitative research that elicits important attributes for the target consumers.

4.      Respondents (target customers) evaluate / rank or rate products. 

Data Matrix = 4 (products) X 6 (attributes) X 582 (respondents).

	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

Factor Analysis: Key Concepts

1.      It is used when it is difficult to get a clear picture of the market when dealing with too many attributes and products.

2.      All the data/dimensions might not be necessary to capture consumer perceptions. 

When the attributes are Highly correlated, we can create linear combination of the measures to get a single new dimension of the original attributes. It will help us reduce no of attributes by taking out attributes on which all objects 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 can be done using commercial software SPSS or SAS or free software like PerMap.

Example Plot of Attributes of Stores on a 2D Perceptual Map

Here

Attribute 1 = Price satisfaction, Attribute 2 = Variety satisfaction,

Attribute 3 =    Organization satisfaction, Attribute 4 = Service satisfaction

Attribute 5 = Item quality satisfaction and Attribute 6 = Overall satisfaction

Guidelines for Interpreting Perceptual Maps

1.      The arrow indicates the direction in which that attribute is increasing.

2.      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 explaining variance.

3.      Attribute that are both relatively important (i.e., long vector) and close to the horizontal (vertical) axis help interpret the meaning of axis.

4.      To represent a store 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).

5.      What practical uses can you now put this map to at this stage?


      Limitations

1.      Researcher should be able to clearly conceptualize the attributes.

2.      No perception gap between intended and actual perception of the attributes.

3.      Works well for hard or functional attributes, (price, product features).

Posted By:
S M Murshid Azam
Group C
Roll No -14104