Advanced strategies for better customer insights

Tom Ellyatt

Towards Data Science

The RFM (Recency, Frequency, Monetary) model, with its simplicity and ease of implementation, remains a great tool for customer relationship management, offering valuable insights into customer behaviour.

Building on the groundwork from my previous article “How to Create an RFM Model in BigQuery”, in this article, we will explore ways of improving the model.

Here’s what we’ll cover in this article:

So, you’ve got your RFM model up and running in BigQuery, sorting your customers into groups like Champions, Potential Loyalists, At Risk of Losing and so on. It’s a great start, but we can kick it up a notch.

While breaking down your customers into these groups tells a nice story, adding what I like to call a Customer Score can reinforce the model with a single, intuitive metric.

Why and What is a Customer Score?

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