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)
History
RFM was originally developed in the direct marketing industry.
Segmentation
Segmentation with RFM is created by grouping different ranges of R and F+M. One way to do it:
| Segment | Recent Score Range | Frequency + Monetary Score Range |
|---|---|---|
| Champions | 4-5 | 4-5 |
| Loyal Customers | 2-5 | 3-5 |
| Potential Loyalist | 3-5 | 1-3 |
| Recent Customers | 4-5 | 0-1 |
| Promising | 3-4 | 0-1 |
| Customers Needing Attention | 2-3 | 2-3 |
| About To Sleep | 2-3 | 0-2 |
| At Risk | 0-2 | 2-5 |
| Can’t Lose Them | 0-1 | 4-5 |
| Hibernating | 1-2 | 1-2 |
| Lost | 0-2 | 0-2 |
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
Implementation
108.30.10.20.20.10.10 Data Analysis - Segments - RFM - How to segment RFM
Variations of RFM model
108.30.10.20.20.10.20 Data Analysis - Segments - RFM - variations
Other models that use RFM
Other prediction models use RFM data - 113.020.050 Statistics - BTYD models - 113.020.050.10 BTYD - BGBB
Models that use RFM for prediction like 113.020.050.10 BTYD - BGBB can be used to predict 108.20.30 Data Analysis - Customer lifetime value.
References: 1. https://www.putler.com/rfm-analysis/ 2. https://clevertap.com/blog/rfm-analysis/ 3. https://www.coursera.org/learn/wharton-customer-analytics/home - Week 3 slides, Fader
Graph:
- 108.30.10.20.20.10 Data Analysis - Segments - RFM to 108.30.10.20.20 Data Analysis - Segments and metrics for outputs
- 108.30.10.20.20.10 Data Analysis - Segments - RFM to 108.30.10 Data Analysis - Structural analysis
- 108.30.10.20.20.10 Data Analysis - Segments - RFM to 108.20.10 Data Analysis - Optimize
- 108.30.10.20.20.10 Data Analysis - Segments - RFM to 108.30.10.20.20.10.10 Data Analysis - Segments - RFM - How to segment RFM
- 108.30.10.20.20.10 Data Analysis - Segments - RFM to 108.30.10.20.20.10.20 Data Analysis - Segments - RFM - variations
- 108.30.10.20.20.10 Data Analysis - Segments - RFM to 113.020.050 Statistics - BTYD models
- 108.30.10.20.20.10 Data Analysis - Segments - RFM to 113.020.050.10 BTYD - BGBB
- 108.30.10.20.20.10 Data Analysis - Segments - RFM to 108.20.30 Data Analysis - Customer lifetime value
- 108.20.07 Data Analysis - Customer analysis primary objectives to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.20.10 Data Analysis - Optimize to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.20.10.40.10 Data Analysis - Which customer segment to give discounts to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.20.20 Data Analysis - Make decisions to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.20.30.10 Data Analysis - Benefits of LTV analysis to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.20.50.20 Data Analysis - Acquitention Phase II to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.30.10.20.20 Data Analysis - Segments and metrics for outputs to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.30.10.20.20.10.10 Data Analysis - Segments - RFM - How to segment RFM to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.30.10.20.20.10.20 Data Analysis - Segments - RFM - variations to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 108.30.10.20.30 Data Analysis - Structural analysis deliverables to 108.30.10.20.20.10 Data Analysis - Segments - RFM
- 113.020.050 Statistics - BTYD models to 108.30.10.20.20.10 Data Analysis - Segments - RFM