pymc-marketing icon indicating copy to clipboard operation
pymc-marketing copied to clipboard

Add `rfm_segmentation` Utility

Open ColtAllen opened this issue 4 months ago • 2 comments

RFM Segmentation is a way to segment customers on their past purchasing behavior. This is a complementary technique to CLV/BTYD modeling as customers in different segments benefit from different marketing strategies, and would be a good bridge between combining MMM and CLV.

A traditional rules-based RFM segmentation would be a straightforward addition, and I also have some ideas on a Bayesian clustering variant.

ColtAllen avatar Feb 09 '24 18:02 ColtAllen

I also have some ideas on a Bayesian clustering variant.

My recent experience with an RFM segmentation project led me to discover the effectiveness of utilizing jenks breaks methodology over simple percentile-based segmentation. I found Jenks breaks logic to offer more meaningful segmentations. I suggest considering Jenks breaks as it could potentially enhance the segmentation process. There is a C-based implementation that can be found here.

sarim-zafar avatar Apr 05 '24 01:04 sarim-zafar

Hey @sarim-zafar,

Thanks for sharing. The Jenks Breaks methodology has some parallels with Dirichlet processes, which can be used to automatically infer the optimal number of clusters.

ColtAllen avatar May 11 '24 19:05 ColtAllen