How the RFM Analysis Can Help You Segment Your Customers

How the RFM Analysis Can Help You Segment Your Customers

One of the most popular techniques for customer base segmentation is the RFM Analysis. RFM segmentation helps you identify groups of individuals for personalized, targeted marketing messaging that will guide them on the appropriate customer journey. By grouping and ranking customers, you can target them with personalized communications that are relevant for them, thus generating a higher response rate and an improved overall customer experience.

This technique is still popular mainly because it’s simple and intuitive, your team can use it without the need for data scientists, and the results are easy to understand and interpret.

RFM stands for Recency, Frequency and Monetary. By analysing these 3 measurable factors, the marketing team can gain a better understanding of customer behavior.


How much time has passed since the customer interacted with the brand? A purchase is usually considered an interaction but you could use other interactions as well: last website visit, last app/product usage, last login, etc. Most businesses measure this in days but you need to customize this to best fit the lifecycle of your customers.

The key question is how much time does it have to pass before you can consider that a customer has become inactive? For instance, in the case of an Italian coffee shop that the neighbors visit each morning for their daily expresso, the owner might start to worry if he doesn’t see one of his neighbors for more than a week.

For your business it might make more sense to measure the recency in months or weeks or even hours. But generally, the expectation is that the more recent the interaction, the better the response or conversion rate will be.


How often has the customer interacted with your brand during a specific period of time? Customers with frequent activities are more engaged and most probably more loyal so it is definitely worth having this in mind when segmenting your customer base.

A frequent shopper will have increased trust in your brand but at the same time she is going to have higher customer experience expectations. Going back to the Italian coffee shop example, the customer will expect you to know her by name and to already know by heart her preferred coffee. 


How much did the customer spend throughout her lifetime or during the last year? Not all customers are created equal so it goes without saying that your big spenders should get increased attention. Not only should you have this in mind when designing customer loyalty programs, VIP subscriptions and marketing campaigns, but this is an important factor that should drive your overall advertising budget.

To fully take advantage of your sales and advertising budgets, you need to always know where your best customers came from so you know where you should invest your marketing efforts to attract more similar customers. 


While this is a general RFM intro, it should give you an overview of the dimensions which we will use for the customers segmentation. In the next article, we will detail how your own customer base should decide what “recent”, “frequent” and “big spender” means!