RFM – Recency, Frequency and Monetary

RFM is a way of ranking your active customers based on profitability and frequency on a scale of 1–5. Your most active customers will get a 5 and the least active ones will get a 1. RFM ranking is a great tool to understand who your top customers are and where to put in extra efforts to increase sales.

The RFM calculation is based on three factors:

  • Recency – How recently the contact made a purchase
  • Frequency – How frequently the contact makes purchases
  • Monetary – How much money the contact has spent

The ranking is calculated regularly on your active customers based on the criteria: Has made a purchase in the last X days (often 365 days). This will determine the amount of days of historical transactions that will be included in the RFM calculations.

In other words:

  • When the last purchase was made during these 365 days
  • How often the customer made a purchase in the last 365 days
  • How much the customer has spent during these 365 days

 

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The top 20 % for each factor will be assigned a 5, the next a 4, and so on. All customers will have a number between 1 and 5 for each factor. This results in many different combinations to use as criteria in your segmentation, analysis or as a valuable input to your overall customer data management.

The model can be used to create a strategy to retain, reward and develop customers. Example:

R F M Classification Action
5 5 5 Top customers Reward
4–5 4–5 2 B customers Motivate purchase
1–2 1–2 1–2 C customers Retain
3 3 3 B customers Develop
3 1–2 4 B customers Drive to store
3 4 4 B customers Develop
3 4 4 A customers Reward
1 2 1 C customers Retain

 

Regular stores based on RFM

Engage has a term called Regular store that is used to connect a customer to a specific store based on their buying behavior (= RFM). To ensure a fair grading, each factor is weighted between 0 and 100 and it is up to you to decide how this should be set up. Example:

RFM.dia.png

If you consider recency, frequency and monetary to be equally important the weighted value will be 33/33/34 for each factor. But if you consider frequency and monetary to be more important than recency the weighted value can be set to 40/40/20.

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