Question
Analyze and determine based on the different Centroid Table and performance Vectors below (Gender and attrition) why is this company is losing customers (attrition rate)
Analyze and determine based on the different Centroid Table and performance Vectors below (Gender and attrition) why is this company is losing customers (attrition rate) by using the primary attribute of gender and attribution rate to identify patterns/reasons that people are leaving ( analyze the data results and identify anomalies or reasons tobelieve people are leaving the company (lack of benefits, high APR, age group)
Centroid Tab
Attributes | Cluster 0 | Clsuter 1 | Cluster 2 | Cluster 3 | Cluster 4 |
Attrition Flag IF Formula = 0 | 0.427233 | 0.051435 | -2.30146 | 0.434464 | -0.05849 |
Attrition Flag IF Formula = 1 | -0.42723 | -0.05144 | 2.301456 | -0.43446 | 0.058494 |
Gender = M | 0.981201 | 0.292862 | -0.12247 | -0.61952 | 0.379255 |
Education_Level = High School | 0.028531 | -0.08261 | -0.02406 | -0.00315 | 0.089852 |
Education_Level = Graduate | -0.00931 | 0.05378 | -0.02427 | 0.007693 | -0.02297 |
Education_Level = College | -0.02738 | 0.010768 | -0.01547 | 0.018719 | 0.085598 |
Education_Level = Post-Graduate | 6.17E-04 | 0.047179 | 0.020685 | -0.01145 | -0.02878 |
Education_Level = Doctorate | -0.01828 | -0.01253 | 0.075796 | -0.01046 | 0.003131 |
Marital_Status = Married | 0.056039 | -0.18527 | -0.04067 | 0.004453 | -0.26062 |
Marital_Status = Single | -0.05841 | 0.130921 | 0.032173 | 0.005523 | 0.274083 |
Income_Category = $60K - $80K | 0.644873 | 0.090775 | -0.07308 | -0.39976 | 0.332027 |
Income_Category = Less than $40K | -0.73642 | -0.26211 | 0.082201 | 0.473212 | -0.3041 |
Income_Category = $80K - $120K | 0.658686 | 0.156513 | -0.03619 | -0.42204 | 0.106038 |
Income_Category = $40K - $60K | -0.33488 | -6.20E-04 | -0.01927 | 0.218947 | -0.13236 |
Card_Category = Blue | 0.26689 | -3.74649 | 0.258771 | 0.266059 | -3.74649 |
Card_Category = Gold | -0.10594 | -0.10594 | -0.10594 | -0.10594 | 9.438283 |
Card_Category = Silver | -0.2375 | 4.080701 | -0.2375 | -0.2375 | -0.2375 |
CLIENTNUM | 0.03115 | 0.042247 | -0.1108 | 0.009742 | -0.00233 |
Customer_Age | -0.02126 | -0.06015 | 0.04536 | 0.008815 | -0.11171 |
Dependent_count | 0.067306 | 0.063707 | 0.040152 | -0.06745 | 0.246741 |
Months_on_book | -0.01883 | -0.04943 | 0.03802 | 0.00681 | -0.04576 |
Total_Relationship_Count | 0.13248 | -0.28388 | -0.34009 | 0.065894 | -0.52912 |
Months_Inactive_12_mon | -0.07595 | -0.07153 | 0.355329 | -0.05257 | -0.03471 |
Contacts_Count_12_mon | -0.03766 | -0.01244 | 0.466738 | -0.11705 | -0.0551 |
Credit_Limit | 0.508504 | 1.869154 | -0.2127 | -0.51704 | 2.206791 |
Total_Revolving_Bal | 0.095958 | 0.059956 | -0.61521 | 0.115801 | 0.267644 |
Avg_Open_To_Buy | 0.499737 | 1.863232 | -0.15736 | -0.5273 | 2.182111 |
Total_Amt_Chng_Q4_Q1 | 0.08459 | 0.015845 | -0.32447 | 0.043592 | 0.053329 |
Total_Trans_Amt | -0.00696 | 0.659254 | -0.45752 | 0.047738 | 0.959032 |
Total_Trans_Ct | -0.0199 | 0.427359 | -0.90068 | 0.224884 | 0.675029 |
Total_Ct_Chng_Q4_Q1 | 0.123564 | -0.02306 | -0.70257 | 0.141265 | -0.01444 |
Avg_Utilization_Ratio | -0.34747 | -0.79338 | -0.37358 | 0.440987 | -0.78704 |
PerformanceVector - Attrition
PerformanceVector: Avg. within centroid distance: -20.495
Avg. within centroid distance_cluster_0: -22.160
Avg. within centroid distance_cluster_1: -29.642
Avg. within centroid distance_cluster_2: -23.017
Avg. within centroid distance_cluster_3: -17.500
Avg. within centroid distance_cluster_4: -28.302
Avg. within centroid distance_cluster_5: -19.414
Avg. within centroid distance_cluster_6: -19.118
Avg. within centroid distance_cluster_7: -22.268
Avg. within centroid distance_cluster_8: -17.330
Avg. within centroid distance_cluster_9: -24.104 Davies Bouldin: -2.137
Cluster Model
Cluster 0: 3027 items
Cluster 1: 550 items
Cluster 2: 1483 items
Cluster 3: 4829 items
Cluster 4: 111 items Total number of items: 10000
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