An Introduction to Predictive Customer Lifetime Value Modeling

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This article provides a basic understanding of predictive customer lifetime value modeling. It defines the concept and explains why such models are also called customer equity models. Probabilistic models will help us define these parameters at the customer level and make inferences about future purchases and value. Machine learning and Markov models are also worthy approaches to CLV modeling, but they need to be tweaked and sometimes customized to fit the particulars of a business situation. The Pareto/NBD model focuses on modeling lifetime and purchase count. Monetary value can be modeled separately from the purchase count and lifetime components of the model. And it concludes by showing how these CLV estimates at the customer level are the way to tie the probabilistic model and the Pareto/NBD model together.

Publication: 
Oracle+Datascience.com
Author: 
Jean-Rene Gauthier
Document Type: 
Research
Paywall: 
Free
Description: 
Accurately predicting a customer's lifetime value can provide your business with key insights. Click to learn more about CLV predictive models.
Meta Title: 
A Beginner's Guide to Customer Lifetime Value Prediction Models

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