Day 6 - Team E

Jai Mohan Singh Sood

Today again we had 2 lectures of our Business Analytics Workshop. So let’s have a look at the day’s proceedings.

Firstly, 4 random students from 4 different groups presented their respective cases on clustering techniques through short PPTs. Each presentation was followed by a brief Q&A session by the students and the professor.

Then a questionnaire regarding the best music download service was put up by the professor. This was used to design the music download service of Nokia Ovi. This survey was done to gauge the customers’ association with music downloads. ‘Probability’ was used as the distance measure. 18 popular music services were used for the questionnaire. When plotted in PERMAP, these brands formed 3 concentric circles, with almost equal distances between each brand in a given circle.

After this we shifted focus back to our favourite ‘Retail’ file. Then a new section called ‘Tables’ was opened. The ‘Store’ variable’s scale was changed from ‘scale’ to ‘nominal’, so that each store can be compared for the various satisfaction parameters. ‘Stores’ was taken in rows and the various satisfaction parameters (6 in total) were taken in the columns. Then the output was generated and copied to Excel, which was then copied and saved in a notepad to upload in PERMAP. 

After uploading the file, ‘Map Evaluation’ was done by checking all ‘active vectors’. The stores which were closer to the various arrowheads (which represented the various service attributes) were found to be rated higher on those particular service parameters. To further narrow down our analysis, the ‘Price’ attribute was removed from the active vectors list. No real change in the mapping was observed but. Thus we concluded that price was not much of a determinant in terms of customer satisfaction. Then individual attributes were chosen and ‘vector tie lines’ was checked to measure which store is actually closer to which attribute. This was done individually for each attribute.

Then a small exercise was done in which every team picked up one variable for analysis. Our team picked ‘Distance from home’. After doing all the needful and plotting the data in PERMAP, we concluded that people living very close to the store (<1 km) came there because of price, variety and overall satisfaction. On the other end of the spectrum, people living very far from the store (>30 km) came to the particular store because of the organization in the store.

At the end each team was given a task to come up with 2 strategies, based on the mappings and crosstab evaluations.

Th-th-th-that's all folks!