RFM, or ‘recency frequency monetary value’ to give it its full name, has long been the targeting tool of choice for the home shopping industry; so we decided to give it a challenge by building as an alternative a propensity model using exactly the same data set.
An RFM score will describe the overall strength of the relationship between a business and a customer, but the question is whether we can improve on that by building a propensity score targeted at a specific purchase activity or category.
A great advantage of RFM scores is that because they are not proposition specific, they can be used across a wide range of applications; however, if the scale of any actual marketing selection is substantial enough, then the extra resource required to build the propensity score may be justified.
In addition, a propensity model can take into account not only RFM based information, but also things like age, gender and other demographic information that might be available on customers.
RFM or propensity score white paper
In this example, we are dealing with data from a home shopping company with over 1m customers, and a large number of merchandise categories. We first used cluster analysis to group the merchandise categories into six high level merchandise groups.
The RFM score was then built on customers buying across all six merchandise groups whereas the propensity model was developed for one specific group. We used those who had purchased from the specific merchandise group in the previous three months as the target variable.
In order to compare the two targeting approaches, we selected deciles within the customer base by each method, and then looked at the proportion of actual buyers that we found within each decile.
Download the RFM or propensity score white paper to find out the results.
UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.
Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.
Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.