RFM Analysis

Smart marketers recognize the significance of "knowing thy customer." Instead of simply focusing on increasing CTRs (Click-Through Rates), marketers must shift their focus to retention, loyalty, and building customer relationships.

Instead of analyzing the entire customer base as a whole, it is better to segment them into homogeneous groups, understand the characteristics of each group, and engage them with relevant campaigns.

RFM analysis is one of the most popular, simple, and effective segmentation methods for marketers to analyze customer behavior.

What is RFM Analysis?

RFM is an acronym that stands for Recency, Frequency, and Monetary value, each of which corresponds to a key customer trait. Because frequency and monetary value affect a customer's lifetime value, and recency affects retention, a measure of engagement, these RFM metrics are important indicators of a customer's behavior.

Businesses that do not have a monetary component, such as viewership, readership, or surfing-oriented products, could use Engagement parameters instead of monetary ones. As a result, RFE, a variant of RFM, is used. This Engagement parameter could also be defined as a composite value based on metrics like bounce rate, visit duration, number of pages visited, time spent per page, and so on.

These facts are illustrated by RFM factors:

• The customer is more responsive to promotions if the purchase was made recently.
• The more often a customer purchases, the more engaged and satisfied they are.
• Money separates high-spending customers from low-cost buyers.

RFM Segmentation Analysis

Let's look at a few interesting sections:

• Champions are your best customers, who have purchased recently, frequently, and in large quantities. Reward these clients. They can be early adopters of new products and promote your brand.
• Potential Loyalists are recent customers who have purchased from you on a regular basis and have spent a significant amount of money. To upsell them and help them become Loyalists or Champions, offer membership or loyalty programs or recommend related products.
• New Customers are customers who have a high overall RFM score but do not shop frequently. Begin building relationships with these customers by offering onboarding assistance and special offers in order to increase their visits.
• Customers who are at risk are those who have previously purchased frequently and in large quantities but have not done so recently. Send them personalized reactivation campaigns to reconnect with them, as well as renewals and useful products to encourage another purchase.
• Can't Lose Them are customers who used to visit and buy frequently but haven't done so recently. Bring them back with relevant promotions, and conduct surveys to figure out what went wrong and keep them from going to a competitor.

In sum

RFM is a data-driven customer segmentation technique that allows marketers to take tactical decisions. It empowers marketers to quickly identify and segment users into homogeneous groups and target them with differentiated and personalized marketing strategies. This in turn improves user engagement and retention.