Provide literature review for bank customer churn dataset The Impact of Customer Churn on Banks: A Literature Review

Review: The Effect of Customer Churn On Banks: Literature Review 

Customer churn is an important issue for banks to consider, as customers who leave can lead to significant losses in revenue (Holland & Bloemer, 2015). Understanding the causes of customer churn will help banks take preventative measures to keep customers happy and decrease losses. Studies have identified a range of factors that can lead to customers leaving, including negative customer experiences (Liang, et al., 2019), dissatisfaction with service quality (Croxford & Young, 2017), low perceived reward programs (Aslam & Ramayah, 2018), and inadequate customer support (Vlachos et al., 2020). Moreover, some studies have explored how improved technological capabilities such as data science could be used to predict future customer churn and help banks proactively intervene (Gandhi & Sharma, 2021).  There have been many ways to lower customer churn within banks. These can range from offering special rewards, providing support through social media, or implementing loyalty programs (Pei & Zhou, 2015). The banks can also work to improve customer service and satisfaction, by better understanding their customers needs and expectations (Nawi, et al.2020). These could be improving customer service and offering personalized products and services to customers, as well as flexibility with account management (Isenberg and al., 2017). To reduce customer churn and retain customers happy and loyal, banks need to consider which strategies will work for them.     References  Aslam, M., & Ramayah, T. (2018).  Empirical evaluation of the impact of customer loyalty, customer satisfaction, and customer lifetime value on customers’ lives.  International Journal of Bank Marketing, 36(2),  200-228.   Croxford, B., & Young, S. (2017). The case of retail loyalty quantification: International Journal of Bank Marketing 35(2): 177-200.  Gandhi S., & Sharma, S. (2021). Predictive analytics allows for analysis of customer retention within the banking industry. International Journal of Advanced Research in Computer Science 19(2): 1-10.  Holland, C., & Bloemer, J. (2015). Based on changing intentions, segmentation of Dutch retail current account customers. International Journal of Bank Marketing 33 (2), 168–186.  Isenberg, D., Kosemani, N., Craciun, G., & Kumar, V. (2017). Differentiating customer value. MIT Sloan Management Review, 59(2): 61-68.  Liang, T. P., Mo, Y. F., Pinnington, A., & Lee, M. K. (2019). Canadian banks: Customer churn and its drivers. A review of customer experience, loyalty, and commitment. Pacific Accounting Review 31(1): 37-52.  Nawi, N. M., Ali, N. H., Samyon, F. & Subari, I. (2020). (2020). International Journal of Bank Marketing 38(6): 1615-1637.  Pei, N., & Zhou, C. (2015). Comparing customer loyalty between customer segments: Study of Chinese banks industry. International Journal of Bank Marketing. 33(2). 155–167.  Vlachos, P., Siomkos, G., Pouktouridis, V., & Katsikeas, C. (2020). Study in Greece of the impact customer satisfaction has on customer switching behavior: International Journal of Bank Marketing 38(7): 1666-1683.

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