First, read carefully the case (Q5_Pacific Brands Case) and look at the data (Q5_Pacific Brands Data).  Answer the following questions.

Q5(A) (2 points)

As described in the case, there are originally 21 variables.  Please choose up to 8 variables as segmentation bases, which in your opinion are more important and meaningful in understanding differences among beer consumers.  Explain why you chose them

Q5(B) (2 points)

Copy 8 variables to Q5_Segmentation Tool (Input Data tab).  You will automatically obtain the results.  To make it simple, I have fixed the result to a 3-segment solution.

Profiling Part #1: describe and characterize the segment in terms of 8 variables you have chosen, which is shown in Output Clusters tab.

This is an important exercise.  To characterize, from the table in Output Clusters, you can compare across columns (which segment has high or low average for each variable) and across row for each segment (which variable is strong or weak for that segment).

Q5(C) (2 points)

From the Output Clusters tab, you can find the segment membership.  Copy and paste the membership information to the last column (labeled as segment membership) of Descriptors tab in Q5_Pacific Brands Data.

Sort the data by segment and get the averages for each segment (your manual work)

Profiling Part #2: describe and characterize the segment in terms of the distinctive variables (descriptors) as you see relevant and meaningful.

Same as before, look across rows and columns for high/low values