Machine Learning for Survival Analysis: A Survey <s> Customer Lifetime Value <s> Abstract Customer lifetime value has been a mainstay concept in direct response marketing for many years, and has been increasingly considered in the field of general marketing. However, the vast majority of literature on the topic (a) has been dedicated to extolling its use as a decision-making criterion; (b) has presented isolated numerical examples of its calculation/determination; and (c) has considered it as part of the general discussions of profitability and discussed its role in customer acquisition decisions and customer acquisition/retention trade-offs. There has been a dearth of general modeling of the topic. This paper presents a series of mathematical models for determination of customer lifetime value. The choice of the models is based on a systematic theoretical taxonomy and on assumptions grounded in customer behavior. In addition, selected managerial applications of these general models of customer lifetime value are offered. <s> BIB001 </s> Machine Learning for Survival Analysis: A Survey <s> Customer Lifetime Value <s> We present and discuss the important business problem of estimating the effect of marketing activities on the Lifetime Value of a customer in the Telecommunications industry. We discuss the components of this problem, in particular customer value and length of service (or tenure) modeling, and present a novel segment-based approach, motivated by the segment-level view marketing analysts usually employ. We describe in detail how we build on this approach to estimate the effects of retention campaigns on Lifetime Value, and also discuss its application in other situations. Our solution has been successfully implemented by the Business Insight (BI) Professional Services. <s> BIB002 </s> Machine Learning for Survival Analysis: A Survey <s> Customer Lifetime Value <s> Thank you for downloading driving customer equity how customer lifetime value is reshaping corporate strategy. As you may know, people have look numerous times for their favorite books like this driving customer equity how customer lifetime value is reshaping corporate strategy, but end up in malicious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some infectious bugs inside their desktop computer. <s> BIB003
Customer Lifetime Value (LTV) BIB001 BIB003 refers to the profit that a customer brings to a retail outlet based on his or her purchase history. In the marketing domain, customer LTV is used to evaluate the relationships between customers and stores. It is important for a store to improve the LTV of its customers in order to maintain or increase its profits over the long term since it is often quite expensive to acquire new customers. In this case, the main goal of this problem is to identify the purchase patterns of customers who have a high LTV and provide recommendations for a relatively new user who has similar interests. Identifying loyal customers using LTV estimation has been studied by various researchers BIB002  ) using survival analysis methods and data mining approaches, both of which are helpful in identifying purchase patterns. In this context, LTV can be defined using a survival function, which can then be used to estimate the time of purchase for every customer from a given store based on store information and also the customer demographic information available in the store's database including, for example, gender, income, and age.