The Iron Rule of RFM

Few rules of thumb are so deeply embedded in our thoughts that we’re surprised to recall that they’re really just rules of thumb, not scientifically proven facts.

And for many, that’s the case for this month’s rule of thumb: the rule of recency, frequency, monetary value (shortened to RFM). As catalogers we use RFM constantly, almost without thinking about it, not because psychologists have proved to us that it should work, but because as marketers we know that it simply does work, day in and day out, and has been working since the earliest days of cataloging.

As with most everyday things though, a closer look turns up a variety of unexpected twists, which we’ll explore in this column devoted to RFM.

Let’s begin by defining the rule:

The “RFM” Rule of Thumb

You’ll get higher response rates when you mail to customers who have (a) bought more recently, (b) bought more often and (c) spent more lifetime dollars.

Conversely, you’ll get lower response rates from mailing to customers who have bought less recently, less often and spent fewer total dollars.

Is RFM obsolete?

If you’re thinking that RFM is too old-fashioned for our post-modern world of neural nets, synergy models and so on, think again. Buzzwords like CHAID, regression, data mining and the like all refer to analytical techniques, but to function, these analytical techniques must be applied to real-world data. And that’s what RFM is—three vital chunks of real-world data that we maintain for each customer, and that we use to predict how they’ll respond to our offers.

In fact, RFM is a central part of the power of most current statistical tools used by catalogers. Take RFM data away, and the power of modern statistics for catalogers would be drastically reduced.

How is RFM measured and stored?