… , we apply the recency, frequency, and monetary (RFM) model and … decision making,
specifically when data involves customer … used customer life-time value factor and customer loyalty …

… an old one, retention becomes even more important. The … on the customer group classified
by RFM model combined with … In the first two parts of this paper, the application of RFM …

… applied to data from a different industry. The company’s own … ) combined RFM variables
with product loyalty to yield better … , decision trees, logistic regression and naïve Bayes) could …

… like Multilayer Perception Neural Network and Naive Bayes. … In this study, we preferred to
apply the scale by Clevertap (2021) … Although having a good trend as a loyal customer, the …

… By interpreting these results, he will provide decision makers … (MLP), Naive Bayes, regression,
J48, the classification results … that a similar technique be applied that enables us to classify …

… applied to data from a different industry. The company’s own … ) combined RFM variables
with product loyalty to yield better … , decision trees, logistic regression and naïve Bayes) could …

… apply business intelligence in identifying potential customers … Naïve Bayes and neural
networks classification approach is … to enhance the decision making for retaining the customers (…

… Naive Bayes classifier or support vectors. Recent studies show the use of modified RFM based
on the application area where client … of a better customer retention approach is required. …

… , and naïve Bayesian [5], they provided valuable insights for strategic decision making. …
can be applied and affect each other to improve customer loyalty and retail sales amount. …

… customers based on the RFM model, then applying the classification, Proportion of accuracy
in customer loyalty … Although the C4.5 algorithm with the k-mean segmentation give a better …