RFM – Recency Frequency Monetary

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Predicting Future Behaviour

The best indicator of future behaviour …. is past behaviour!

Did you do it before? You are likely to do it again

Did you do it often? You are more likely to do it again

Did you do it recently? You are likely to do it again soon!

Past Behaviour doesn’t tell us everything – but if you already have a database, it is probably your most accessible & cost-effective data source

Recency Frequency Monetary, or RFM, is a method of analyzing past customer behaviour, with a view to predict their future behavior.

Metrics: Recency Frequency Monetary (RFM)

The Question:

What simple ways are there to predict if customers will buy again?

Approach:

Analyze when they last purchased, how many times they have purchased, and how much they bought

Commentary:

Past behaviour is the best indicator of future behavior. In the direct mail days, RFM was more important (because of higher variable costs). It is less used now, but still useful for segmenting.

 

RFM Methodology

 

Recency = When was the last time you shopped

  • For Recency we reverse order the database from cardholders who have visited most recently, to those who haven’t visited for the longest time. Divide into 5 equally sized sub-segments, and give a value from 5 (most recent) to 1 (least recent)

Frequency = how often have you shopped

  • For Frequency we reverse order the database from cardholders who have shopped the most often, to those who have shopped the least. Divide into 5 equally sized sub-segments, and give a value from 5 (most frequent) to 1 (least frequent)

Monetary = how much have you spent

  • For Monetary we reverse order the database from cardholders who have spent the most, to those who have spent the least. Divide into 5 equally sized sub-segments, and give a value from 5 (most spend) to 1 (least spend)

Remember to eliminate the statistical outliers, who will skew the results.

 

Standard Industry Reponse Rates (Historical)

Recency 5 (R5) = 3.49%

Recency 4 (R4) = 1.25%

Recency 3 (R3) = 1.08%

Recency 2 (R2) = 0.63%

Recency 1 (R1) = 0.25%

Frequency 5 (F5) = 1.99%

Frequency 4 (F4) = 1.56%

Frequency 3 (F3) = 1.31%

Frequency 2 (F2) = 0.92%

Frequency 1 (F1) = 0.93%

Monetary 5 (M5) = 1.62%

Monetary 4 (M4) = 1.45%

Monetary 3 (M3) = 1.20%

Monetary 2 (M2) = 1.21%

Monetary 1 (M1) = 1.23%

 

 

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