Customer lifetime value allows Banks and Financial Institutions to examine the worth of customers to the business, which provides important inputs to take informed marketing & retention decisions and better Customer Relationship Management. Traditional CLV approaches are primarily isolated at account level worthiness. Some Customer level CLV do take 360° view of the customer relationships but are more heuristic in nature or predicting the CLV based on historical CLV data using single model approach. In this paper, we have explored the existing solutions available to calculate the CLV and explained the rationale for not using with their respective limitations. The focus of the study was on retail banking sector, the proposal is to use whole gamut of existing marketing and risk predictive models for calculating the predicted CLV without taking the time value of money into consideration. It also discusses about the comparisons between the present and future CLV of the customer and how to check the overall health of the bank’s business using calculated CLV.
CITATION STYLE
Channa, H. S. (2019). Customer lifetime value: An ensemble model approach. In Advances in Intelligent Systems and Computing (Vol. 808, pp. 353–363). Springer Verlag. https://doi.org/10.1007/978-981-13-1402-5_27
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