Current Volume 9
Abstract
Customer churn is a significant challenge in the banking industry because retaining existing customers is substantially more cost-effective than acquiring new ones. This study analyzes customer churn patterns using segmentation-driven analytics on a European banking dataset containing 10,000 customers from France, Spain, and Germany. The objective is to identify customer segments with elevated churn risk, evaluate demographic and financial factors associated with churn, and provide actionable recommendations for improving customer retention. The analysis focuses on geography, age groups, credit score bands, tenure categories, account balances, customer activity, and product ownership. Findings indicate that customer engagement, geography, age, and financial profile significantly influence churn behavior. The study concludes with strategic recommendations for targeted retention programs and customer relationship management initiatives.
Citations
IRE Journals:
Pavan Arvind Giri "Customer Segmentation and Churn Pattern Analytics in European Banking" Iconic Research And Engineering Journals Volume 9 Issue 12 2026 Page 2450-2453 https://doi.org/10.64388/IREV9I12-1718879
IEEE:
Pavan Arvind Giri
"Customer Segmentation and Churn Pattern Analytics in European Banking" Iconic Research And Engineering Journals, 9(12) https://doi.org/10.64388/IREV9I12-1718879
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