Question

# As part of the quarterly reviews, the manager of a retail store analyzes the quality of...

As part of the quarterly reviews, the manager of a retail store analyzes the quality of customer service based on the periodic customer satisfaction ratings (on a scale of 1 to 10 with 1 = Poor and 10 = Excellent). To understand the level of service quality, which includes the waiting times of the customers in the checkout section, he collected data on 100 customers who visited the store; see the attached Excel file: ServiceQuality.

1. Using Data Mining > Cluster, apply K-Means Clustering with the following Selected Variables: Wait Time (min), Purchase Amount (\$), Customer Age, and Customer Satisfaction Rating. In Step 2 of the k-Means Clustering procedure, normalize(standardize) input data, assume k= 5 clusters, 50 iterations, and Fixed start with the default Centroid Initialization seed of 12345. In Step 3, select the checkboxes “Show data summary” and “Show distances from each cluster center”.
1. What is the most homogenous cluster? What is the number of customers in this cluster? For this cluster, what is the average standardized Euclidean distance between its observations and its centroid (center)? What is the centroid of this cluster (expressed in standardized data)?Using the cluster centroids, how would you characterize the customers in the most homogenous cluster in comparison with the customers in the remaining clusters?
2. Which two clusters are most distinct and why? Using their centroids, how would you compare the customers of the two clusters?
2. Using Data Mining > Cluster, apply Hierarchical Clustering with the following Selected Variables: Wait Time (min), Purchase Amount (\$), Customer Age, and Customer Satisfaction Rating. In Step 2 of the Hierarchical Clustering procedure, normalize(standardize) input data and apply Ward’s clustering method, while in Step 3, select the checkboxes “Show dendrogram”, “Show Cluster Membership”, and assume k= 5 clusters.
1. Show the obtained dendrogram.
2. What are the sizes of the created clusters?
3. What are the centroids of the created clusters expressed in original data.
 Customer Number Wait Time (min) Purchase Amount (\$) Customer Age Customer Satisfaction Rating 1 2.3 436 42 7 2 2.8 408 33 6 3 3.2 432 38 5 4 3.4 431 40 5 5 3.4 456 29 6 6 4.2 537 46 4 7 3.2 456 42 5 8 1.4 430 40 8 9 6.4 663 24 3 10 7.8 839 37 4 11 6.5 659 52 5 12 9.8 836 43 2 13 5 543 56 4 14 1.8 419 35 8 15 6.1 700 39 6 16 3.4 432 44 7 17 7.8 845 33 5 18 2.8 467 42 6 19 1.2 425 46 8 20 9.5 848 50 4 21 8.2 808 55 3 22 7.6 674 35 3 23 5.4 547 52 4 24 6.7 691 38 5 25 9.6 847 53 4 26 11.4 826 48 2 27 2.1 426 52 7 28 5.6 535 32 7 29 3.7 521 43 8 30 4.9 513 44 6 31 6.4 645 53 5 32 9.3 846 52 4 33 10.6 730 51 3 34 6.5 786 53 3 35 5.4 523 46 5 36 7.6 654 36 6 37 3.2 443 48 7 38 2.4 409 54 8 39 1 400 39 6 40 0.2 418 51 7 41 2.4 498 30 6 42 5.7 532 32 5 43 6.4 663 44 7 44 6 681 39 8 45 3.7 543 54 5 46 8.7 800 51 5 47 6.9 673 45 5 48 9.8 856 43 4 49 10 756 44 4 50 9.5 854 43 6 51 6.3 672 50 6 52 7.4 698 47 7 53 2.3 434 43 7 54 4.6 544 40 4 55 4.9 523 53 6 56 5.7 546 55 6 57 7.4 676 42 8 58 6.8 662 36 6 59 9.6 1000 40 5 60 6.4 678 46 5 61 7.2 655 32 4 62 5.6 535 36 5 63 9.7 833 35 3 64 2.3 498 30 7 65 4.3 508 41 6 66 5.7 542 49 6 67 2.4 435 39 8 68 6.7 665 41 5 69 2.4 387 54 9 70 9.8 845 34 7 71 4.5 532 40 6 72 6.7 687 30 5 73 7.2 643 33 4 74 3.5 424 49 7 75 8.9 836 47 5 76 9.7 876 31 4 77 3.5 456 47 7 78 4.7 523 49 6 79 8.5 818 35 5 80 9.7 845 54 4 81 2.7 401 55 7 82 5.7 554 43 6 83 7.6 648 51 7 84 4.4 540 31 6 85 7.8 839 45 5 86 9.4 845 48 4 87 4.9 534 36 5 88 7.1 693 44 4 89 5.4 512 39 3 90 6.7 665 49 5 91 8.6 825 36 5 92 4.5 548 30 7 93 6.1 704 31 5 94 5.3 509 31 6 95 6.7 672 35 5 96 8.1 824 36 4 97 6.3 632 30 4 98 7.4 689 35 2 99 8.8 839 50 4 100 9.6 847 35 2

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