Below is the results of segmentation analysis output of the data provided with the Kirin case. As you see, we use a 4-segment solution Cluster Sizes The following table lists the size of the population and of each segment, in both absolute and rela Size /Cluster OverallCluster 1 Cluster 2 Cluster 3 Cluster 4 100 10.2050.315 Number of observations 82 70 65 Pro ion 0.259 0.221 Segmentation Variables Means of each segmentation variable for each segment Segmentation variable/Cluster OverallCluster 1 Cluster 2 Cluster 3 Cluster 4 Rich full-bodied Light beer No aftertaste Refreshitn 3.48 6.08 4.27 4.46 5.23 2.3 7.03 4.82 6.29 4.56 5.02 3.46 s down easil 2.91 2.63 0.443 3.13 7.09 4.88 7.51 Gives a "buzz" 2.82 taste Low 3.41 4.44 value 6.77 From c Attractive bottle Prestigious brand with brewing tradition 3.82 4.42 4.45 4.94 7.06 5.74 4.68 4.03 6.05 6.42 6.54 7.05 6.26 2.44 2. 2.67 1.87 4.48 6.02 5.21 2.67 2.58 6.26 5.02 6.17 Drink at picnics 4.56 4.62 2.49 Masculine 2.13 2.49 1.33 Drink with friends Drink at home To serve dinner guests For dining out Drink at bar 4.57 1.36 4.92 5.03 4.35 5.06 1.46 3.57 5.69 Based on these results, how would you describe the charactersitics/preferences of the people in each segment? AND based on these characteristics, how would you name each segment