What is RFM analysis?
Ravi Gondaliya avatar
Written by Ravi Gondaliya
Updated over a week ago

What is RFM (recency, frequency, monetary) analysis?

Usually, we segment customers based on events they perform like abandoned Cart, Dint purchase in few months, and so on. But when it comes to segmenting your all customers based on activities they perform on their entire life cycle, the best way to do it is using RFM analysis.

RFM(Recency, Frequency, and Monetary) analysis is a marketing technique used to rank and group customers into different segments based on how recently they have purchased, how frequently they are purchasing, and how much they are spending.

The RFM technique assigns each customer numerical score based on these factors to provide an objective analysis. RFM analysis is based on the marketing theory that "80% of your business comes from 20% of your customers".

What Are the Benefits of an RFM Analysis?

RFM analysis helps you to group your entire customer database and helps you to improve customer retention and increase overall customer lifecycle value. With RFM analysis, you can get answers that matter the most to your revenue growth:

  • How many customers we may lose this month? How much revenue they were generating?

  • How many customers are close to being our loyal customers?

  • How much of the revenue our loyal customers are generating?

How does RFM score calculation work?

RFM analysis gives a score to each customer based on three factors: recency, frequency, and monetary.

  • Recency: How recent was the customer's last purchase?

  • Frequency: How often customer made the purchase in a given period?

  • Monetary: How much money did the customer spend in a given period?

Based on the above three factors, a score from 1 to 5 is given to each customer, with 5 being the highest. The collection of these three parameter values for each customer is called an RFM segment/group.

Understanding an RFM Segments

Instead of simply using an overall RFM average value to identify the best customers, you can use RFM analysis to identify segments of customers with similar values called RFM segments.

You can use these segments for targeted marketing campaigns on different marketing channels. Some examples of customer types include:

  • Can Not Lose Them: Users who were active at one point in your site/app, but haven’t been back recently. Strong candidates to re-engage.

  • At-Risk: Users having above-average frequency but low recency. Strong candidates to re-engage.

  • Hibernating: Users having the lowest recency and frequency scores. You may lose these customers.

  • Loyal Customers: Users with the highest frequency of use with strong recency.

  • Champions: Most active users, having the highest recency and frequency scores.

  • Need Attention: Most active users, having highest recency and frequency scores.

  • And so on.....

Doing RFM analysis in Growlytics

Click here to learn how you can do RFM analysis in Growlytics.

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