Perceptual mapping is a graphical approach used to visually display the perceptions of customers or potential customers. It is also called as multi dimension scaling (MDS). Perceptual maps can have any number of dimensions but the most common is two dimensions. More than two can be very difficult to analyze and collect data as it will become complex.
The picture shows the perception of a car buyer, the way he looks at different companies.
Perceptual mapping is of two types. They are:
1) Overall similarity
2) Attribute based
Overall similarity is a mapping in which we have to know the objects to actually evaluate the similarity between them. It is a complex mapping as it needs the evaluator to know the objects in detail.
Attribute based mapping demands the attributes to be mentioned beforehand. This makes the job a lot easier for the evaluator as he knows exactly on what parameters he has to compare the objects on. The main disadvantage here is that as we concentrate on a single parameter, we forget other important parameters which have significant importance.
Enough of the theory! Practical approach is a more prominent approach to learn. Isn’t it?
For the first time in 6-7 classes we were asked to stay away from SPSS for a while. This is a pleasant surprise. We were asked to work on different software called “PERMAP”. Luckily this turned out to be a lot easier and “user friendly”.
PERMAP’s fundamental purpose is to uncover any “hidden structure” that might be residing in a complex data set. It takes object-to-object proximity values which here are similarities, dissimilarities, distances, correlation etc to calculate proximities and also uses MDS to make a map that show the relationship between the objects.
PERMAP has a big circle in the center and all we need to do is to open a text file into this software. Now this text file is something which has to be worked on. This text file contains our perception about the object. To help understand, we took an easy perception of laptop manufacturing companies. Here, we were asked to take the combination of 6 different companies which resulted in 15 combinations. We assigned each combination a value in the range 0-9 where 0 mean opposite and 9 means very much comparable. This resulted in 15 values for 15 combinations. All the experiments are taken and averaged. This resulted in 15 final values. These values are then put into a matrix formed with the same row and column heads i.e. laptop companies. The resulting pyramid form is then transferred as it is to a text file. We then put a title for the text file and also mentioned the number of objects used.
We have got 6 circles showing the 6 laptop companies in PERMAP. This graphical representation actually made sense as we analyzed the placement of circles. Apple, a company out of the six we chose, remained far off as we perceived it to be the most desired and quality laptop. The only company that came close to Apple is Sony, which we thought is close to Apple in terms of quality and aesthetics.
This shows that the complexity is reduced to a great extent as the data is presented in a graphical format as it is easy to comprehend. This is a good practical learning. Looking forward to apply this to many tasks that we come across every day.
Group Name: Finance 2
Author Name: Abhishek Reddy