Perceptual mapping is a research technique utilising
a special questionnaire design and an advanced statistical analysis method. It
gives a picture of the competitive landscape from the customer’s viewpoint and
identifies the aspects that customers use to compare products and decide
amongst them. Use of this tool is widespread with it being suitable for use to address
issues like reasons why certain brands are preferred over another and why
customers link certain brands together etc. It helps to identify competitor’s strengths
and weakness and could give necessary steps to improve business strategy
accordingly.
Why this tool is useful over the traditional tools
is that while ratings and ranking s are useful ways to understand products and
service differences most customers do not work though a list of criteria before
they take a decision about the product or organization. As such the tool does the
following:
1)
It
determines how a customer simplifies factors or aspects to differentiate
competitors. These are used to create
the axis in the map.
2)
It
shows position of competitors relative to each other, and particularly the
distance from one competitor to another.
The concept behind the perceptual mapping is an
analytical technique called multi dimensional scaling (MDS).MDS is a set of
data analysis technique that displays the structure of distance like data as a
geometrical picture.
MDS originated from physco- metrics where it was
designed to help understand why people chose on similarity of member from a set
of objects.MDS pictures data sets that approximate the distances between the
pairs of objects. The data are called similarities, dissimilarities, distances
or proximities must reflect the amount of dissimilarity between pairs.
Each object or event is represented by a point in a
multidimensional space. The points are arranged in this space so that the
distances between pairs of points have the strongest possible relation to the
similarities among the pairs of objects. That is, two similar objects represent
two close points while two dissimilar objects represent two points that are far
apart. The space is usually a two- or three-dimensional Euclidean space, but
may be non-Euclidean and may have more dimensions. MDS is a generic term that
includes many different specific types. These types can be classified according
to whether the similarities data are qualitative (called nonmetric MDS) or
quantitative (metric MDS). The number of similarity matrices and the nature of
the MDS model can also classify MDS types. This classification yields classical
MDS (one matrix, unweighted model), replicated MDS (several matrices,
unweighted model), and weighted MDS (several matrices, weighted model).
In short although the other techniques are useful
too in understanding the rating of products or company this tool is useful in
giving a visual depiction of the factors and as such would make it easier for a
person to comprehend the data.
Done By Rohith Emmanuel (Group B)
Roll no: 14043
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