How can you use RFM analysis for effective customer segmentation?

1 What is RFM analysis?

RFM stands for Recency, Frequency, and Monetary value. These are three metrics that measure how recently, how often, and how much a customer has purchased from your business. RFM analysis is a technique that assigns a score to each customer based on these metrics, and then groups them into segments based on their scores. For example, a customer who has bought from you recently, frequently, and with a high value would have a high RFM score, and would belong to a segment of loyal and valuable customers.

2 How does RFM analysis work?

To perform RFM analysis, you need to have data on your customers' purchase history, such as the date, amount, and frequency of their transactions. This data can be stored in a spreadsheet, a database, or a software tool to calculate the RFM scores for each customer. The process involves four steps: first, define the time period for your analysis, such as the last 12 months, and filter your data accordingly; second, calculate the recency (number of days since the last purchase), frequency (number of purchases in the time period), and monetary value (total amount spent in the time period) for each customer; third, assign a score from 1 to 5 to each customer for each metric - 5 being the highest and 1 being the lowest - using equal intervals, percentiles, or custom ranges to define the scoring criteria; fourth, combine the scores for each metric to create a RFM score for each customer. For example, a customer with a recency score of 5, a frequency score of 4, and a monetary value score of 3 would have a RFM score of 543.

3 How can you use RFM analysis for customer segmentation?

Once you have the RFM scores for each customer, you can use them to create customer segments based on their behavior and value. You could define your segments by the average, median, or quartile of the RFM scores, or the combinations of the individual scores. For example, Champions are customers with high RFM scores (e.g., 555, 554, 545), who are loyal and valuable buyers. Loyal customers have high frequency scores (e.g., 445, 454, 544), while New customers have high recency scores but low frequency and monetary value scores (e.g., 511, 512, 513). At-risk customers have low recency scores but high frequency and monetary value scores (e.g., 311, 312, 313). However, you can create more or less segments depending on your business goals and customer base. The main idea is to use RFM analysis to identify and understand your different customer groups, and then design strategies to retain and grow them.