外文翻譯--預(yù)測(cè)電信行業(yè)客戶流失——基于一種sas生存分析模式的應(yīng)用程序-全文預(yù)覽
【正文】 cedure produces parametric regression models with censored survival data using maximum likelihood estimation. The PHREG procedure is a semiparametric regression analysis using partial likelihood estimation. PROC PHREG has gained popularity over PROC LIFEREG in the last decade since it handles time dependent .However if the shapes of survival distribution and hazard function are known, PROC LIFEREG produces more efficient estimates (with smaller standard error) than PROC PHREG does. SAMPLING STRATEGY On August 16, 2020, a sample of 41,374 active highvalue customers was randomly selected from the entire customer base from a telemunications pany. All these customer were followed for the next 15 months. Therefore August 16, 2020 is the origin of time and November 15, 2020 is the observation termination time. During this 15month observation period, the timing of customer churn was recorded. For each customer in the sample, a variable of DUR is used to indicate the time that customer churn occurred, or for censored cases, the last time at which customers were observed, both measured from the origin of time (August 16, 2020). A second variable of STATUS is used to distinguish the censored cases from observed cases. It is mon to have STATUS = 1 for observed cases and STATUS = 0 for censored cases. In this study, the survival data are singly right censored so that all the censored cases have a value of 15 (months) for the variable DUR. DATA SOURCES There are four major data sources for this study: block level marketing and financial information, customer level demographic data provided through a third party vendor, customer internal data, and customer contact records. A brief description of some of the data sources follows. Demographic Data – Demographic dada is from a third party vendor. In this study, the following are examples of customer level demographic information: Primary household member’s age Gender and marital status Number of adults Primary household member’s occupation Household estimated ine and wealth ranking Number of children and children’s age Number of vehicles and vehicle value Credit card Frequent traveler Responder to mail orders Dwelling and length of residence Customer Internal Data – Customer internal data is from the pany’s data warehouse. It consists of two parts. The first part is about customer information like market channel, plan type, bill agency, customer segmentation code, ownership of the pany’s other products, dispute, late fee charge, discount, promotion/save promotion, additional lines, toll free services, rewards redemption, billing dispute, and so on. The second part of customer internal data is customer’s telemunications usage data. Examples of customer usage variables are: Weekly average call counts Percentage change of minutes Share of domestic/international revenue Customer Contact Records – The Company’s Customer Information System (CIS) stores detailed records of customer contacts. This basically includes customer calls to service centers and the pany’s mail contacts to customers. The customer contact records are then classified into customer contact categories. Among the customer contact categories are customer general inquiry, customer requests to change service, customer inquiry about cancel, and so on. MODELING PROCESS Model process includes the following four major steps. Explanatory Data Analysis (EDA) – Explanatory data analysis was conducted to prepare the data for the survival analysis. An univariate frequency analysis was used to pinpoint value distributions, missing values and outliers. Variable transformation was conducted for some necessary numerical variables to reduce the level of skewness, because transformations are helpful to improve the fit of a model to the data. Outliers are filtered to exclude obser
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