Customer segmentation is a critical step toward appropriately differentiating services to different customers. One common way of segmenting customers is by using what is called Recency, Frequency, Monetary (RFM) approach, where customers are classified based on the recency of their transactions as well as how often they purchase goods and services and how much money they spent. However, this approach is not able to fairly differentiate customers especially when it comes to the cases where old customers have decreased or stopped their purchases and the new customers just started buying. In order to overcome this, we proposed what is called Multi Layer Recency, Frequency, and Monetary (MLRFM) approach. In this approach, we divide time periods into multiple layers and the recency, frequency, and monetary values are analyzed considering these different segments. Our numerical examples show that this multi layer approach can provide a good alternative for the companies that sell products online and customers are behaving very dynamically.
- online transaction
- recency frequency monetary