I am trying to segment our customers based on their purchase data. And I came to know about the RFM technique (Recency, Frequency and Monetary) through these posts here, here etc.
Recency - How recently they made a purchase
Frequency - How many times they made a purchase
Monetary - How much revenue did company got from that customer
I also came across a python package called
while I understand the idea of RFM, I am confused as to why do the consider
average revenue of a customer (from all his/her transactions) instead of
Total revenue for all his/her transactions?
For ex: If a new customer places 2 huge orders for 100K and 200K, then he contributed 300K to the company and could be classified as "New but promising" or "New but Heavy spender" etc.
But doesn't taking average normalize everyone on the equal scale? So, then monetary value doesn't become useful metric to segment customers. Instead we have to use only Recency and Frequency (because they have raw values).
Is there any reason why you think average revenue is better than Total revenue?