R - Beyond the Basics

1 Measuring the value of a customer within the RFM framework.

1. Measure the recency, frequency, and monetary value of customer purchases.
2. Set a score to rank customers according to their purchase recency, frequency, and monetary value.
3. Calculate the overall RFM score.
4. Analyze RFM group differences.

The data:

1.1 Step 1: Measure the recency, frequency, and monetary value

All RFM measures have to be measured on the individual customer level:

• Recency = difference in days between the latest purchase and today.
• Frequency = number of transactions.
• Monetary Value = average amount spent per transaction.

-------------------------------------------
 Customer   recency   frequency   monetary 
---------- --------- ----------- ----------
  149332     2257         3          92    

  172951     1411         4         222    

  120621     1878         1         100    

  149236     2007         2          60    

  140729      225         6          67    

  180970     1269         2          74    
-------------------------------------------

Table: RFM Values

1.2 Step 2 : Set a score to rank customers

• Recency: The higher the recency measure, the lower the score.

• Frequency: The higher the frequency measure, the higher the score.

• Monetary Value: The higher the monetary value measure, the higher the score.

-------------------------------------------
 Customer   recency   frequency   monetary 
---------- --------- ----------- ----------
  149332       1          3          3     

  172951       2          3          3     

  120621       1          1          3     

  149236       1          2          2     

  140729       3          3          2     

  180970       2          2          2     
-------------------------------------------

Table: RFM scores

1.3 Step 3 : Calculate the overall RFM score

RFM scores can be either unweighted or weighted:

• The unweighted score takes the simple average over all scores.
• The weighted score takes a weighted average over the scores, e.g. 60-20-20.

1.3.1 An unweighted overall score for all customers

\(RFM.Score(unweigthed) = 1/3*recency + 1/3*frequency + 1/3*monetary\)

1.3.2 A weighted overall score which weighs frequency more heavily

\(RFM.Score(weigthed) = 0.2*recency + 0.6frequency + 0.2*monetary\)

1.4 Step 4 : Analyze RFM group differences

Based on their RFM scores, customers can be divided into target groups.

Customers with the maximal score: