RFM: the customer segmentation model

All too often companies focus on publishing content and reports, while neglecting what really makes business thrive: customers. Knowing your customers and their spending habits is crucial for business growth. The RFM model plays a central role in this.
The RFM model, which stands for Recency, Frequency, Monetary, is a marketing segmentation strategy based on customer behaviour. It divides the public according to purchase history and purchase pattern, answering these questions:

  • When did the customer last make a purchase?
  • How often does the customer purchase something?
  • How much has the customer spent?

RFM is a model for segmenting customers, analysing purchasing behaviour and automating marketing and sales processes based on the data obtained. It analyses each customer on the basis of three fundamental pieces of information:

  • Purchase recency: indicates the last time a customer placed an order, categorising the period as long, medium or short term;
  • Frequency: represents how often the customer makes purchases, classifying it as normal, casual or frequent;
  • Monetary value: shows the amount spent by the customer in a given time period, divided into categories such as spender, average, saver.

Segmentation of this kind makes it possible to design a much more efficient marketing strategy, optimise sales and marketing expenditure and formulate targeted engagement strategies.

RFM segmentation: benefits and uses

The RFM model is used to:

  • increase customer loyalty by detecting a decrease in their purchase frequency and launching engaging campaigns;
  • increase customer lifetime value (CLV) and profits by targeting up- and cross-selling campaigns at the most loyal users;
  • optimise activation costs by adjusting the discount amount for future purchases according to customer value;
  • customise real-time communications across all marketing channels, including e-mail marketing, website and social media.

RFM segmentation: how it works and segment types

The RFM model makes it possible to differentiate customers in each of the three dimensions: Recency, Frequency, Monetary. Based on the specific values identified for each variable, the model creates more or fewer segments. For example, after having established a certain sum, customers will be considered savers or spenders if they have spent or not spent a certain amount over a set period of time. The same reasoning applies to the other two dimensions.

Below are some examples of RFM customer segments:

  • Best customers: these are the customers who score the highest in each category. They are brand loyal, high spenders and inclined to repurchase again quickly. They actively respond to loyalty programmes and show interest in new product launches. For this segment, it is inadvisable to offer price discounts, as they are brand loyal. Instead, opt to increase their CLV by suggesting items based on past purchases;
  • “Spendthrift” customers: this segment only includes customers with the highest monetary value scores, as it is based solely on the monetary metric. An effective strategy for this cluster is to offer luxury products, higher subscription levels and value-added upselling in order to increase the average order value. Again, the application of discounts is not advisable;
  • Loyal customers: this segment only takes purchase frequency into account. Although they buy regularly, loyal customers are not necessarily high-spending. You could therefore reward them with free shipping, discounts or other types of offers. Another way to engage them is through advocacy programmes, such as writing reviews: customers who score highly in terms of purchase frequency but low in terms of monetary value tend to respond better to product recommendations based on past purchases, as well as to incentives linked to spending thresholds, such as a free gift for transactions above the average order value;
  • At-risk customers: these are the customers who used to stand out as big spenders and/or loyal, but now have low recency and frequency scores. Marketers should consider sending messages aimed at building loyalty, such as special discounts, exclusive offers and new product launches.

Conclusion

The RFM model proves crucial in identifying the needs of different customer segments. Using this method, marketers can set up triggers that initiate automated processes as soon as a user joins a new group.

This is a reliable and effective method for assessing contacts and ensuring customer loyalty over time.

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