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RFM Customer Segmentation Model - Model Scenario

Wouldn't be great to tailor your marketing strategy regarding identified groups of customers? That way, you can target each group with personalized offers, increase profit, improve unit economics, etc.

RFM Customer Segmentation Model identifies customers based on three key factors:

  • Recency - how long it’s been since a customer bought something from you, or visited your website
  • Frequency - how often a customer buys from you, or how often he visits your website
  • Monetary - the average spend of a customer per visit, or the overall transaction value in a given period of time

Let's go through the RFM analysis inside Graphite. The dataset on which you will run your RFM Model must contain a time-related column, given that this report studies customer behavior over a period of time. We need to distinguish all customers, so we need an identifier variable like Customer ID. If you might have data about Customer Names, great, if not, don't worry, just select the same column as in the Customer ID field. Finally, we need to choose the numeric variable regard to which we will observe customer behavior, called Monetary (amount spent).

That's it, you are ready to run your first RFM Model. With RFM Model you can develop, sustain, or improve customer relationships, trial your product pricing, and strengthen your profitability or customer retention. In the next post, we will talk more about the model results, so stay tuned. 🙂

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