RFM Analysis: A Comprehensive Guide to Customer Segmentation

Saksham

What is RFM Analysis?

RFM (Recency, Frequency, Monetary) Analysis is a customer segmentation technique that uses three key metrics:

  1. Recency: How recently a customer made a purchase
  2. Frequency: How often they purchase
  3. Monetary: Total amount spent

Statistical Approach to Binning in RFM

Binning is critical in RFM to categorize customers:

  • Divide each metric into quartiles (4 equal segments)
  • Assign scores 1-4 for each dimension
  • Create customer segments based on combined scores

Python Example:

R Example

Customer Segments Created

  1. Champions: High scores across R, F, M
  2. At Risk: High historical value but haven’t purchased recently
  3. Hibernating: Low scores in all dimensions
  4. New Customers: High recency, low frequency/monetary

References

  • Specifically referenced from:
    • Blattberg, R. C., & Deighton, J. (1996). Customer Equity Framework
    • Kumar, V., & Reinartz, W. (2016). Customer Engagement Marketing