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RFM Models Customer Segmentation - Results

RFM Models - Results

As we now know how to run RFM models analysis in Graphite, let's go through the Model Results. The results consist of 6 tabs: Recency, Frequency, Monetary, RFM Analysis, RFM Matrix, and Details Tabs. All results are visualized because a visual summary of information makes it easier to identify patterns than looking through thousands of rows.


According to the Recency factor, which is defined as the number of days since the last purchase, we divide customers into 5 groups:

  • lost
  • lapsing
  • average activity
  • active
  • very active.

In the Recency Tab, we observe the behavior of the above groups, such as the number of customers, average monetary, average frequency, and average recency per group.


As Frequency is defined as the total number of purchases, customers can buy

  • very rarely
  • rarely
  • regullary
  • frequently
  • very frequently.


Monetary is defined as the amount of money the customer spent, so the customer can be a

  • very low spender
  • low spender
  • medium spender
  • high spender
  • very high spender.

In the Frequency and Monetary Tabs, you can track down the same behavior of the related groups, as with the Recency Tab.

RFM models analysis ranks every customer in each of these three categories on a scale of 0 (worst) to 4 (best). After that, we assign an RFM score to each customer, by concatenating his numbers for Recency, Frequency, and Monetary value. Depending upon their RFM score, customers can be segregated into the following categories:

  • lost customer
  • hibernating customer
  • can-not-lose customer
  • at-risk customer
  • about-to-sleep customer
  • need-attention customer
  • promising customer
  • new customer
  • potential loyal customer
  • loyal customer
  • champion customer.

All information related to the above groups of customers, such as the number of customers, average monetary, average frequency, and average recency per group, can be found in the RFM Analysis Tab.

rfm models
RFM Models Customer Segmentation - Results 2

RFM Matrix

The RFM Matrix Tab represents a matrix, showing the number of customers, monetary sum and average, average frequency, and average recency (with breakdown by Recency, Frequency, and Monetary segments). All the values related to the first five tabs, with much more, can be found on the Details Tab, in the form of a table. 

Collect your data and start exploring your customers' behavior: finding the right stability between focusing on new and existing customers is leading to brand trust and loyalty. 🙂

Want to Run and Share your Data Predictions with your team?
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