Example of #1 was in the advice to treat the annuals and the PAYG differently. Clearly these are two different behaviors and scoring them together is just going to muck the joint up.

On #2, that’s why I’m not a very big fan of “traditional RFM” - there’s too much chance for people to screw it up *unless* they’re using it for a one-off purpose - like mailing a catalog. Much prefer the LifeCycle Grids approach, which is similar to keeping track of monthly RFM scoring at the customer level but a lot easier to understand - I think, anyway!

1. I agree that there is no point in segmenting to the nth degree prior to scoring, especially to someone who is just starting on things like RFM. However, just based on my experience I will stress on some segmentation “if there are distinct customer groups in terms of behavior”. As an example, it is possible that because of the nature of products or service a company offers, certain industries are more frequent users of the products/service. That does not [by default] make the customers in other industries any less valuable — purely on the basis of RFM. Just bringing this up as I have see many folks creating an RFM model without adequate thought and coming to wrong conclusions on who are ‘good’ customers and who are ‘risky/defecting’ customers.

2. The second point is on current value. Again, I agree with you that current value is a measure of customer value. However, just as before I want to caution users that one has to look at current value keeping (a) the customer profile in mind (e.g industry as mentioned above), and (b) the customer’s past value. If one is doing a RFM scoring frequently then this is less of an issue. However, if someone creates a one-time RFM model they can wrongly classify a customer as ‘low-value’, when the truth is that the customer is a ‘high-value’ customer but on the declining life-cycle (giving their business to competition).