Advanced strategies for better customer insights
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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:
- How to Create Customer Score
- Alternative RFM Banding Methods
- Adding Milestones to the Model
- Expanding the Model to Include Email Engagement
- Building a Monthly RFM Model and Backdating Past Months
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.