RFM Analysis

RFM is a database marketing technique originally developed and used in direct marketing and retail industry. This approach can be used in any industry to support marketing and sales decisions for developing marketing and sales strategies and tactics.

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RFM tool is used for analyzing customer behavior and identifying customer groups with similar behaviors. Different customer groups or RFM segments behave differently on different marketing approaches such as promotions and advertising so RFM helps marketing managers develop customized marketing strategies for different RFM segments.

RFM also helps with identifying who are the best / most profitable customers and who are the customers who are more likely to respond to a certain marketing strategy. RFM Analysis is a simple quantitative approach and gives marketing managers business insight into their customer base.

RFM Tool for Excel Users


How RFM works?

1. R – Recency – when was the last time customers purchased from us

2. F – Frequency – how often customers purchase from us

3. M – Monetary – how much customers spend with us

For example, each of these three variables can be divided into five groups and marketing managers can analyze customer behavior for the last 12 months. So R value of 5 would be assigned to a customer who purchased in the last 73 days and R value of 1 would be assigned to a customer who last purchased more then 292 days ago.

Similar to R values, the Fand M values would be assigned based on how many times a customer purchased in the last 12 months and how much they spent for the last 12 months. Generally RFM segments with higher RFM scores are more profitable and loyal to the company.

The best customers are those who are more likely to purchase again and those are customers with higher RFM values. For example RFM customer segment with score of 555 means that they purchased recently, they buy often, and they have big orders. Each customer would be assigned a 3-digit value starting from 111 to 555.


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