A wholesale distributor wants to understand the purchasing profiles of its clients. If a finite set of distinct profiles were defined, then a marketing strategy could be designed specifically for each set of similar clients. The company has compiled a data set that includes annual client spending on diverse product categories. You have been tasked with analyzing the data to determine what patterns emerge and how these patterns can be used to create specific client marketing profiles.

Use k-means clustering to explore and analyze the data set by using only the quantitative variables to cluster the clients.

• Question 1: Explain the process you used to define the clusters, such as the number of clusters formed, the specific variables used, etc. Include the "Cluster Sizes" and "Predictor Importance" outputs when submitting the answer.
• Question 2: Interpret the clusters with respect to the quantitative variables that were used in forming the clusters. Include the "Clusters" output when submitting the answer.
• Question 3: Discuss whether there is a pattern in the clusters with respect to the qualitative variables (i.e., Client_Type or Region). Include the charts illustrating these patterns when submitting the answer.
• Question 4: Provide an appropriate name for each cluster using any or all of the variables in the data set.
• Question 5: Based upon your analysis, what patterns emerged and how can these patterns be used to create specific client marketing profiles? Include discussion of the characteristics for each profile. Present your findings in the form of a 250-word executive summary that includes relevant data, charts, and tables to validate the conclusions presented.