Cluster Analysis Problem

39963Descriptive Statistics. Analyze customer behavior by calculating the following key statistics in Excel:
Variability (Standard Deviation, Range)
Balance Distribution: Do account balances vary widely?
Campaign Contacts: Were some customers over-contacted?
Categorical Breakdown
Marital Status: Percentage of married, single, and divorced customers.
Education Level: Percentage of primary, secondary, and tertiary education levels.
Cluster Distribution: Percentage of customers in each cluster.
2. Cluster Analysis Review. Examine how each cluster differs basked on:

Demographics: Average age, marital status, and education.
Engagement: Contact frequency, response rate. 
Term Deposit Likelihood: Which cluster is most responsive? 
Balance Differences: Do High-Value customers have significantly larger balances? 
Campaign Contacts: Are High-Value customers contacted more often? 
Response Rate: Which cluster had the highest “Yes” rate? 
3. Visualizations for Cluster Comparisons. Use Excel charts to present key insights:

Bar Chart: Show marital status or education level by cluster.
Box Plot or Histogram: Compare balance across clusters.
Scatter Plot: Show the relationship between balance and campaign contacts.
4. Comparative Analysis. Compare customer engagement and behavior across clusters:

Compare Two Clusters (High-Value vs. Low-Value)
Behavior: How does engagement differ? 
Engagement Patterns: Which cluster is more responsive? 
Demographic Influence: Are factors like age or marital status affecting engagement? 
Identify Key Factors Driving Customer Engagement
Balance: Do higher balances correlate with more engagement? 
Campaign Contacts: Does frequent outreach help? 
Previous Outcome: Does a past “Success” predict future engagement?
Use Basic Statistical Tests 
Correlation: Relationship between balance & response rate
T-tests: Are the differences in balance or response rates across clusters significant?
5. Strategic Recommendations. Based on your findings, provide three targeted strategies to improve the bank’s marketing efforts.
The bank is experiencing low customer engagement with its term deposit offerings. Your analysis should address:

How can the bank improve engagement with the right customers?
What customer characteristics influence campaign success?
Which customer segments are most likely to open a term deposit?

What recommendations would you make for each customer segment (High-Value, Moderate-Value, Low-Value)?
How should the bank adjust its approach to increase engagement?
What specific marketing tactics could be most effective for each segment?
Submission

Submit a 3–4 page analysis in Microsoft Word (excluding the cover page, reference list, tables, graphs, and appendices).
Your report should be written from the perspective of a data analyst providing actionable insights to improve the bank’s marketing strategy. Ensure your analysis is clear, data-driven, and tailored to business decision-makers.
Your submission must be your own original analysis, demonstrating your ability to interpret data, generate insights, and develop strategic recommendations.
All recommendations should be supported by data from the analysis and, where applicable, credible external sources. Use proper APA citations to reference industry reports, academic research, or relevant business frameworks that support your conclusions.
Use 12-point Times New Roman or 11-point Arial, 1-inch margins, and double-spacing throughout the document.
Include tables and graphs with proper labeling of figures, numbers, and statistics. All visualizations should be formatted according to APA guidelines.

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