Research trends in customer churn prediction: A data mining approach

This study aims to present a very recent literature review on customer churn prediction based on 40 relevant articles published between 2010 and June 2020. For searching the literature, the 40 most relevant articles according to Google Scholar ranking were selected and collected. Then, each of the articles were scrutinized according to six main dimensions: Reference; Areas of Research; Main Goal; Dataset; Techniques; outcomes. The research has proven that the most widely used data mining techniques are decision tree (DT), support vector machines (SVM) and Logistic Regression (LR). The process combined with the massive data accumulation in the telecom industry and the increasingly mature data mining technology motivates the development and application of customer churn model to predict the customer behavior. Therefore, the telecom company can effectively predict the churn of customers, and then avoid customer churn by taking measures such as reducing monthly fixed fees. The present literature review offers recent insights on customer churn prediction scientific literature, revealing research gaps, providing evidences on current trends and helping to understand how to develop accurate and efficient Marketing strategies. The most important finding is that artificial intelligence techniques are are obviously becoming more used in recent years for telecom customer churn prediction. Especially, artificial NN are outstandingly recognized as a competent prediction method. This is a relevant topic for journals related to other social sciences, such as Banking, and also telecom data make up an outstanding source for developing novel prediction modeling techniques. Thus, this study can lead to recommendations for future customer churn prediction improvement, in addition to providing an overview of current research trends.info:eu-repo/semantics/acceptedVersio

A data-driven approach to improve customer churn prediction based on telecom customer segmentation

Numerous valuable clients can be lost to competitors in the telecommunication industry, leading to profit loss. Thus, understanding the reasons for client churn is vital for telecommunication companies. This study aimed to develop a churn prediction model to predict telecom client churn through customer segmentation. Data were collected from three major Chinese telecom companies, and Fisher discriminant equations and logistic regression analysis were used to build a telecom customer churn prediction model. According to the results, it can be concluded that the telecom customer churn model constructed by regression analysis had higher prediction accuracy (93.94%) and better results. This study will help telecom companies efficiently predict the possibility of and take targeted measures to avoid customer churn, thereby increasing their profits.Numerous valuable clients can be lost to competitors in the telecommunication industry, leading to profit loss. Thus, understanding the reasons for client churn is vital for telecommunication companies. This study aimed to develop a churn prediction model to predict telecom client churn through customer segmentation. Data were collected from three major Chinese telecom companies, and Fisher discriminant equations and logistic regression analysis were used to build a telecom customer churn prediction model. According to the results, it can be concluded that the telecom customer churn model constructed by regression analysis had higher prediction accuracy (93.94%) and better results. This study will help telecom companies efficiently predict the possibility of and take targeted measures to avoid customer churn, thereby increasing their profits.info:eu-repo/semantics/publishedVersio

DataSheet1_Wenshen-Jianpi prescription, a Chinese herbal medicine, improves visceral hypersensitivity in a rat model of IBS-D by regulating the MEK/ERK signal pathway.docx

The goal of the study was to analyze whether WJP can alleviate visceral hypersensitivity in IBS-D model rats. In this study, 36 Sprague–Dawley (SD) rats aged 4 weeks old were randomly divided into two groups: the model group (n = 27) and the control group (n = 9). The rat model of IBS-D was established by modified compound methods for 4 weeks. After the modification, IBS-D rats were randomly divided into three groups, namely, the IBS-D model group (n = 9), the positive drug group (n = 9), and the WJP group (n = 9), with different interventions, respectively. The control group was fed and allowed to drink water routinely. The Bristol stool scale scores were used to assess the severity of diarrhea. Abdominal withdrawal reflex (AWR) scores were used to assess visceral sensitivity. Expression of TNF-α was measured, and histopathological examinations were performed to assess colon inflammation in IBS-D model rats. Key factors of the MEK/ERK signal pathway in the tissue of the colon and hippocampus were measured to analyze the mechanism of WJP. Compared with the control group, the Bristol stool scale scores in the model group were significantly increased (p < 0.0001). The scores of the WJP group were significantly decreased compared with the model group (p = 0.0001). Compared with the control group, AWR scores in the model group at each pressure level were significantly increased (p = 0.0003, p < 0.0001, p = 0.0007, and p = 0.0009). AWR scores of the WJP group were significantly decreased compared with the model group (p = 0.0003, p = 0.0007, p = 0.0007, and p = 0.0009). Compared with the control group, the model group had significantly higher expression of TNF-α in the colon tissue (p < 0.0001). However, the WJP group had significantly lower level of TNF-α compared with the model group (p < 0.0001). Meanwhile, compared with the control group, the relative expression of the proteins of p-MEK1/2, p-ERK1, and p-ERK2 in the colon tissue was significantly increased in the model group (p < 0.0001). Compared with the model group, the relative expression of the proteins in the colon tissue were significantly decreased in the WJP group (p < 0.0001, p = 0.0019, and p = 0.0013). Compared with the control group, the relative expression of the proteins of p-MEK1/2, p-ERK1, and p-ERK2 in the hippocampus tissue were significantly increased in the model group (p < 0.0001). Compared with the model group, the relative expression of the proteins in the hippocampus tissue were significantly decreased in the WJP group (p = 0.0126, p = 0.0291, and p = 0.0145). The results indicated that WJP can alleviate visceral hypersensitivity in IBS-D model rats, possibly mediated by downregulating the expression of TNF-α, p-MEK1/2, p-ERK1, and p-ERK2 in the colon tissue. At the same time, WJP also affects downregulating the expression of p-MEK1/2, p-ERK1, and p-ERK2 in the hippocampus tissue.</p