RFM = Recency, Frequency, Monetary Value
RFM is a useful model to group a customer base into segments.
Every customer has their own pattern of transactions over time. Some transact all the time in every period, others purchase and then never come back. Recency and Frequency are the best indicators of whether a customer will transact again. (1)
- Recency = How recently did the customer last transact?
- Frequency = How many times did the customer transact in the measured periods?
- Monetary Value = How much money has this customer spent in total?
RFM is a good tool for customer segmentation (as part of the 108.30.10 Data Analysis - Structural analysis)
RFM was originally developed in the direct marketing industry.
Segmentation with RFM is created by grouping different ranges of
F+M. One way to do it:
|Segment||Recent Score Range||Frequency + Monetary Score Range|
|Customers Needing Attention||2-3||2-3|
|About To Sleep||2-3||0-2|
|Can’t Lose Them||0-1||4-5|
When mapped in a grid it looks like this:
Useful business problems to solve with RFM segmentation
Segmenting the customer base with RFM is a fabulous way to identify who/what to optimize.
108.20.10 Data Analysis - Optimize
Variations of RFM model
Other models that use RFM
3. https://www.coursera.org/learn/wharton-customer-analytics/home - Week 3 slides, Fader