Chord Commerce Data Platform
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Predictive Models
Customer Lifetime Revenue (CLR...

Recency, Frequency, Monetary Value (RFM)

3min

Introduction

We are thrilled to present our latest revenue prediction tools for customer segmentation. In this discussion, we will delve into the RFM framework, which stands for recency, frequency, and monetary value. We will also explore customer lifetime revenue and forecast customer re-engagement.



RFM is a proven approach that evaluates a customer's recency, frequency, and monetary value. We examine the time since the customer's last purchase to determine recency. On the other hand, frequency is the total number of purchases the customer makes.

Finally, monetary value refers to the total amount the customer spends in all company interactions. We can effectively segment our customer population by considering all three factors together.

Interpreting RFM Scores

One approach is to assign each customer in your base a ranking of one to five for each of the three measures - monetary, frequency, and recency. A rank of one for monetary represents customers who have spent the highest amount, whereas a rank of five corresponds to those in the lower 20th percentile of spending in the customer base.

Similarly, for frequency, a rank of five would indicate customers who have only made a single purchase. In contrast, a rank of one would tell those who have completed four or more purchases, although this may vary for different stores.

Once we have ranked the customers based on these measures, we can utilize these scores to indicate our progress over time. We can start with a static snapshot of the average RFM score of the company and monitor the progress over time. The goal is to encourage customers to engage more frequently and spend more money. By achieving this, we can move customers towards higher frequency and greater spending, increasing customer engagement.