Predict Customer Lifetime Value with Machine Learning
All Customers are Not Equal
“It is the time you have wasted for your rose that makes your rose so important.”
― Antoine de Saint-Exupéry, The Little Prince
Introduction
As a data scientist working in marketing, I find it quite challenging to combine a few fields like marketing, machine learning and statistics, and produce insights, which make sense. In this blog post, I want to show an application of machine learning in marketing, particularly, in defining and predicting Customer Lifetime Value (CLTV). We will start with the definition of CLTV, then we will explore and analyze a dataset with transactions of online retail, and predict CLTV using linear regression in Python.
Customer Lifetime Value (CLTV)
Customer Lifetime Value (CLTV) represents the total amount of money a customer is expected to spend in a business during his/her lifetime. This is an important metric to monitor because it helps to make decisions about how much money to invest in acquiring new customers and retaining existing ones [1]. Knowing CLTV helps to build marketing…
