4.3 Lifetime Duration

The biggest concern in customer duration modeling is to predict whether customers will repurchase or not in a non-contractual setting, such as in the retailing industry, and whether customers will renew a contract or not in a contractual setting, such as in the telecommunications industry. The estimation of duration is also essential for the calculation of CLV, which is an important metric for customer selection and optimal marketing resource allocation. Logit and probit models are still the most popular and simple modeling methods ever used. The multinomial logit model is another similar method when researchers are to model customers' repurchase choice among several alternatives, such as different stores. To model the timing and occurrence of leaving, survival analysis which models the hazard of lapsing is by nature a suitable modeling method. Survival analysis gives the instantaneous probability of customers lapsing at time t, which is also called the hazard rate, conditional on non-lapsing having occurred. In some cases, researchers consider that a customer's shopping trips occur at discrete-time points, such as days or weeks, and the discrete-time hazard model will be used to model the probability that the purchase event will occur at discrete time t. The proportional hazards model, which does not specify any functional form for the baseline hazard, is another widely used technique in duration data modeling. This model is chosen because of its attractive ...

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