Aditya Kannan

HR Batch 2011-2013

Group G

In today’s class of business analytics we worked on the retail file of SPSS. We were working on the overall store satisfaction. We chose certain required variables such as price, variety and organization satisfaction. We used custom table, chose ordinal to get the mean for the variables. Following is the custom table result I got on SPSS.

		Price satisfaction	Variety satisfaction	Organization satisfaction	Service satisfaction	Item quality satisfaction	Overall satisfaction
		Mean	Mean	Mean	Mean	Mean	Mean
Store	Store1	3.007	3.082	3.253	3.178	3.171	2.986
	Store2	3.206	3.096	2.941	2.875	3.309	3.000
	Store3	3.159	3.094	3.232	3.297	3.080	3.312
	Store4	2.969	3.037	3.315	3.006	3.080	3.068

The numbers have been left to 3 decimal points.

After getting the above data we used the software Permap which is giving extra information and helps us in further analysis. Through Permap we are specifying the relationship between different variables, different price points on the products offered. We found that customers have some amount of autonomy, so they are happy.

We were analyzing on the kind of diagram we would get and implications on the business. We tried to analyze the satisfaction of customers as regards to the arrangement in the store, how organized it is. We discussed the reasons behind the dissatisfaction among customers. We discovered that price is longer a differentiating factor. We worked on the effect on service and variety. Price satisfaction is not really important, stores cannot be differentiated in terms of the prices as they can be the same in all three stores.

We worked on the company brand perception between (national ones) Ultratech, Ambuja, Acc, Orient, Anjani and Zuari. We used the overall similarity method. We tried to find how nationalized the brands are considered by customers, how similar they are.

We also worked on different kinds of music channels used on the internet by people. We tried to find what customers associate with music downloads such as limewire, yahoo music, mesh, bia2, ovi, google, amorphous, itunes, napster, youtube and rhapsody, which are very popular. We worked on how they should be designed, the distances between them in permap. We tried to calculate the  distances between brands, what are lagging behind and what can be added.

We worked on how to make them different from the others, the strategy to be followed in achieving this motive. The strategy could be to differentiate from the others, or to make them similar to the others. Strategy is a matter of perception, all possible alternatives, supporting with first level, then it can be more realistic. Distances, are a measure of probability in permap.

For the Retail.sav file we saw that variables such as age, gender, shopping frequency, mode of payment can be used in mapping them on the software. We tried to see what difference is it if we map different ones.