July 18, 2017

Recency, Frequency, Monetary

I was recently asked to evaluate how a catalog selects names for upcoming mailings. The Executive told me that her vendor asked her company to switch from model-based selections to ... are you ready for this ... to RFM ... prompting me to offer a predictable response.


And I laughed and laughed. What idiots! My goodness. The vendor community is really failing my client base ... again.

One problem.

In my arrogance, I forgot the original request - to evaluate how this company should select names for catalog mailings.

So I evaluated models against the RFM strategy.

The RFM strategy performed to within 0.3% of the prior modeling strategy - a modeling strategy that while not outstanding was at least credible.

Why would a 40 year old methodology perform almost as well as a credible regression-based modeling strategy? Several reasons.
  1. The annual repurchase rate of reactivation candidates at the margin is only about 7% in this example. When repurchase rates are low, RFM is competitive.
  2. The organic percentage is about 40%. So if the annual repurchase rate is just 7% at the margin, and 40% of the 7% will happen with/without aid of catalogs, then the effective annual repurchase rate is actually (1 - 0.40)*0.07 = 4.2%. A lower effective annual repurchase rate makes RFM more competitive.
Instead of judging a vendor for using a 40 year old methodology, I should have judged my pre-conceived notion that I am right and a vendor is wrong. I should have let the data make the case for using the methodology.