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Author: Admin | 2025-04-28
Effectiveness (for example, resource allocation decisions), such automation is highly desirable. The authors describe how model-based automated decision making is likely to penetrate various marketing decision-making environments.The article proposes a DM framework for CLV framework. The framework uses genetic algorithm-based clustering. The framework automates two decisions: first, it automatically segments customers on the basis of CLV, making as distinct segments as possible. The framework decides the number of clusters. Second, the framework chooses among the set of input variables the most important variables to give distinct customer segments.LITERATURE REVIEWOn the basis of the review of CLV metric papers,4, 12 the metrics can be divided into two broad classes as follows: Metrics calculating the total value contributed by a particular customer or a segment of customers; this classification can be further sub-classified as metrics for individual customers and metrics for customer portfolio. Metrics calculating the value contributed by a customer at the time of acquisition, retention or expansion. One set of metrics13, 14 have calculated CLV for individual customers. Few metrics take into account past transactions and inactivity of the customer.14, 15 The other set of CLV metrics are given for a cohort of customers.12, 16 These help in analyzing the effects of elements of marketing on the long-term value of the firm's customer base, to calculate profitability from a growing customer base and to give a metric to gauge revenue from a cohort of customers at different relationship stages. A common drawback with these metrics is that the customer heterogeneity is not represented in the metrics.The other set of CLV metrics is one in which value from customer acquisition, customer retention and customer expansion (cross-selling or margin) is calculated.2, 17, 18 In these metrics, either a component of CLV such as acquisition or retention is represented, or a link between two components is shown. The main drawback with them is that they cater to only a portion of CLV, and not CLV of a customer as a whole. Thus, the value of a customer, throughout her lifetime, is not captured. In addition to the aforementioned drawbacks of each set of
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