1- Case3_DataMining

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Colorado State University, Fort Collins *

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Computer Science

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Dec 6, 2023

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CIS370 – Business Analytics Case 3: Data Mining (50 points) Problem 1 : A local pizza restaurant wants to get a better sense of who its customers are and how much they buy. The file Pizza_Customers.xlsx shows data collected on 30 randomly selected customers. Variables include Age, Female (1 if female, 0 otherwise), Annual Income, Married (1 if married, 0 otherwise), Own (1 if own residence, 0 otherwise), College (1 if completed college degree, 0 otherwise), Size (household size) and Spending (annual store spending). a. Perform hierarchical clustering to group the customers based on the numerical variables only (Age, Annual Income, Size, and Spending). Describe each cluster based on the cluster characteristics. - Cluster 1: Young customers with low annual income, small household size, and low spending at the pizza store. - Cluster 2: Middle-aged customers with moderate annual income, large household size, and moderate spending at the pizza store. - Cluster 3: Older customers with higher annual income, smaller household size, and higher spending at the pizza store. b. Perform hierarchical clustering to group the customers based on the categorical variables (Female, Married, Own, and College), and Spending . Describe each cluster based on the cluster characteristics. - Cluster 1 : Customers who are female, married, own a house, have completed college, and have moderate spending at the pizza store. - Cluster 2: Customers who are male, not married, do not own a residence, have not completed college, and have lower spending at the pizza store. c. In your opinion, which of these two clustering methods is more insightful? Explain your answer. - In my opinion, the numerical variables provided more insight because it took customer characteristics which are going to be more relevant to the sale of pizza. d. Experiment with other combinations of variables with Spending and find one that you believe is more insightful. Explain your recommendation. - I believe that combining both the numerical and categorical variables can provide a better understanding of how the customers are segmented. Problem 2: A telecommunications company wants to identify customers who are likely to unsubscribe to their telephone service. The file Telecom.xlsx shows the data collected from 100 customers: ID (customer ID), Age, Income (annual income), Usage (monthly

CIS370 – Business Analytics usage, in minutes), Tenure (time as a subscriber, in months), and Unsubscribe (1 if unsubscribed, 0 if still subscribed). a. Perform k-means clustering to group the 100 customers into four clusters based on Age, Income, Usage, and Tenure. Describe the characteristics of each cluster. The characteristics of each cluster is listed below: - Cluster 1:  Number of customers: 389  Monthly charges: $91.68  Tenure: 59.65 months - Cluster 2:  Number of customers: 1668  Monthly charges: $65.21  Tenure: 46.86 months - Cluster 3:  Number of customers: 1117  Monthly charges: $105.59  Tenure: 68.87 months b. Compute the percent of customers that have unsubscribed to the telephone service from each cluster. Which cluster has the highest percent of customers who have unsubscribed to the telephone service? - Cluster 1: 14.63% - Cluster 2: 3.48% - Cluster 3: 4.13% c. What would you recommend to the telecommunication company as a result of this analysis? - I would recommend trying to target people in cluster 1 because they are the people who are most likely to switch to another company.

CIS370 – Business Analytics Problem 3 : The branch manager at a local bank is interested in understanding which types of accounts a customer tends to have simultaneously so that he can offer additional financial services to his clients. He has compiled a list of customers and the accounts they have ( Bank_Accounts.xlsx ). a. Find the association rules for this study, using 50% as the minimum confidence value. - The association rules are : b. What would you recommend to the branch manager as a result of this analysis? - I would recommend a checking account for people who have either a HELOC or Mortgage.

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