RFM Concept (EN)

Owned by Danny Esveldt
Last updated: May 10, 2022
3 min read

What is RFM?

RFM stands for Recency, Frequency, and Monetary value. Within our platform, each representing the following;

  • Recency: How recently a customer has made a certain purchase

  • Frequency: How often a customer has made a purchase

  • Monetary value: How much (money) a customer spends on average

These three metrics are key to get a better understanding on a customer's behaviour, for instance;

  • If you want to know more about a customer's lifetime value, you can check the Frequency and Monetary value.

  • If you want to know more about a customer's engagement with your website, you can check the Recency, which affects the retention of a customer.

 

How do we measure RFM?

Now that we have explained what RFM stands for, the next step is to provide some information on how we measure RFM;

  • Once a week, we measure all (RFM) statistics off all your customers who made a purchase in the 365 days prior to the date of the measurement.

  • Important to note is that an RFM score is based on segmentation, where in our case, we split up eacht metric in 5 segments (see table below);

  • With all of your customers (eligable for analysis) being placed in these segments, you can get a clear picture of what type of customer an individual is.

  • For instance; a person who places a big order of 300 EUR once every season, will have a lower F-Score and a higher M-Score than a person who places an order of 50 EUR once every month.

 

RFM Analysis Example

To get a better understanding on how exactly an RFM analysis work, we will take a look at the following customer set:

 

Recency (R-Score)

To determine the R-score of the customer set above we can sort the recency numbers, rank these and them split them up in 5 segments. The customers who most recently bought something will receive the highest R-Score. As shown in the table below:

 

Frequency (F-Score)

To determine the F-Score, we apply the same principle as the R-Score:

 

Monetary Value (M-Score)

To determine the M-Score, we apply the same principle as the R-Score and F- score:

 

RFM Score

Now that we have the individual metrics in order, we can determine the RFM Score:

 

Conclusion

Since we have all of our numbers in place, we can now draw several conclusions from the analysis, for instance;

  • Customer ID 10 is one of our best customers. This customer is a heavy spender, and shops quite often. It's been a while though, since this customer's last order. So it might be a good idea to engage with this customer and recommend some products (via email for instance).

  • Customer ID 1 is a new customer, you can tell by the fact that this customer has very recently bought something, and has only bought something once.

  • Customer ID 5 is a customer at risk, since you can tell that this customer hasn't made a purchase in a long time, but has frequently made purchases.