Open AccessExamining Selected Theoretical Distributions of Life Expectancy to Analyse Customer Loyalty Durability. The Case of a European Retail Bank
Author(s) -
Dominik Kubacki,
Robert Kubacki
Publication year - 2020
Publication title -
acta universitatis lodziensis. folia oeconomica
Language(s) - English
Resource type - Journals
eISSN - 2353-7663
pISSN - 0208-6018
DOI - 10.18778/0208-6018.349.05
Subject(s) - weibull distribution , econometrics , loyalty , life expectancy , loyalty business model , expectancy theory , set (abstract data type) , parametric statistics , proportional hazards model , actuarial science , statistics , business , economics , computer science , marketing , mathematics , sociology , demography , population , management , service quality , programming language , service (business)
One of the key elements related to calculating Customer Lifetime Value is to estimate the duration of a client’s relationship with a bank in the future. This can be done using survival analysis. The aim of the article is to examine which of the known distributions used in survival analysis (Weibull, Exponential, Gamma, Log‑normal) best describes the churn phenomenon of a bank’s clients. If the aim is to estimate the distribution according to which certain units (bank customers) survive and the factors that cause this are not so important, then parametric models can be used. Estimation of survival function parameters is faster than estimating a full Cox model with a properly selected set of explanatory variables. The authors used censored data from a retail bank for the study. The article also draws attention to the most common problems related to preparing data for survival analysis.