Modelling customer lifetime value in contractual settings
نویسندگان
چکیده
منابع مشابه
Customer Lifetime Value Prediction in Non-Contractual Freemium Settings: Chasing High-Value Users Using Deep Neural Networks and SMOTE
In non-contractual freemium and sharing economy settings, a small share of users often drives the largest part of revenue for firms and co-finances the free provision of the product or service to a large number of users. Successfully retaining and upselling such high-value users can be crucial to firms’ survival. Predictions of customers’ Lifetime Value (LTV) are a much used tool to identify hi...
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Being able to measure customer value is a prerequisite for effective customer relationship management and data-driven marketing strategy, as it allows to maximize return on marketing investment, particularly when resources are limited. While past profitability is certainly a useful metric, it is insufficient when trying to predict which customers are going to be most valuable in the future so a...
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Customer lifetime value (LTV) estimation involves two parts: the “survival” probabilities and profit margins. This article describes the estimation of those probabilities using discrete-time logistic hazard models and that of profit margins is based on linear regression. In the scenario when outliers are present among margins, we suggest applying robust regression with PROC ROBUSTREG.
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ژورنال
عنوان ژورنال: International Journal of Services Technology and Management
سال: 2011
ISSN: 1460-6720,1741-525X
DOI: 10.1504/ijstm.2011.042595