In marketing terms, RFM stands for Recency, Frequency, and Monetary Value. It is a data-driven marketing analysis technique used to segment customers based on their purchasing behaviour. RFM analysis helps businesses identify and target customer segments with distinct characteristics, allowing them to tailor marketing strategies and campaigns more effectively.
Here’s a breakdown of the RFM components:
- Recency: This refers to how recently a customer has made a purchase. Customers who have made a purchase more recently are generally considered to be more engaged and responsive. Recency values are often assigned based on the number of days since the customer’s last purchase.
- Frequency: Frequency measures how often a customer makes purchases within a given time period. Customers who make frequent purchases are considered more loyal and valuable to the business. Frequency values can be calculated by counting the number of transactions made by a customer during a specific timeframe.
- Monetary Value: Monetary Value represents the amount of money a customer has spent on purchases. It reflects the customer’s contribution to revenue and indicates their potential value. Monetary values can be calculated by summing up the total monetary value of all transactions made by a customer.
By combining these three metrics, RFM analysis assigns a score or segment to each customer. For example, a common scoring method assigns a value of 1 to 5 for each RFM component, with 5 indicating the highest engagement or value. Customers are then grouped into segments based on their RFM scores, such as “Champions” (high RFM scores) or “Hibernating” (low RFM scores).
RFM analysis provides insights into different customer segments and their behaviors. It helps businesses identify their most valuable customers, target customers for specific marketing campaigns, personalize offers based on customer preferences, and re-engage inactive or dormant customers. RFM analysis can also be combined with other customer data, such as demographics or product preferences, for even more targeted and effective marketing strategies.
