How to make customer segmentation? Recency, Frequency, Monetary (RFM) model

RFM Analysis—Recency, Frequency, Monetary—is a tool to segment customers based on their buying habits. This helps product managers identify and target key customer groups. Here’s how to use RFM Analysis:

Components of RFM

1. Recency: How recently a customer made a purchase.

2. Frequency: How often a customer makes a purchase.

3. Monetary: How much money a customer spends.

Steps to Perform RFM Analysis

1. Data Collection: Gather data on customer purchases. Include the date of each transaction, the number of transactions, and the total amount spent.

2. Score Calculation: Assign scores to each customer for recency, frequency, and monetary value. Typically, scores range from 1 to 5, with 5 being the best.

3. Segment Creation: Combine the scores to create RFM segments. For example, a customer with a score of 5-5-5 is highly valuable, while one with a score of 1-1-1 is less so.

4. Analysis: Study the segments to see customer behavior and value.

Practical Steps for RFM Analysis

1. Prepare Data: Make sure your customer data is accurate and complete. Include details like customer ID, transaction dates, and purchase amounts.

2. Calculate Scores: For each customer, calculate the recency, frequency, and monetary scores.

3. Combine Scores: Create a combined RFM score for each customer. For example, a score of 4-3-5 means high monetary value but moderate recency and frequency.

4. Segment Customers: Group customers based on their RFM scores. Typical segments might include high-value customers, frequent buyers, and recent purchasers.

Benefits of RFM Analysis

1. Identify Top Customers: Recognize which customers are most valuable based on their spending habits.

2. Targeted Strategies: Develop specific plans for different customer segments, such as rewarding top spenders or re-engaging inactive customers.

3. Customer Retention: Focus efforts on keeping high-value customers by seeing their purchase habits.

Example of RFM Segmentation

- Champions: High scores in all three areas. These are your best customers.

- Loyal Customers: High frequency and monetary scores but not necessarily recent buyers.

- Big Spenders: High monetary value but may not buy often.

- At Risk: Customers who used to buy frequently but haven't purchased recently.

- Lost Customers: Low scores in all areas. These customers are unlikely to return.

Tools for RFM Analysis

1. Spreadsheets: Simple tools like Excel can be used for basic RFM analysis.

2. CRM Systems: Many customer relationship management systems have built-in RFM analysis features.

3. Specialized Software: Tools specifically designed for customer analytics can provide more advanced insights.

Using RFM Analysis helps product managers identify key customer segments and tailor their strategies accordingly. The focus is on real customer data, resulting in better decision-making and improved customer retention.