Jim answers more questions from fellow Drillers
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Q: I purchased your book and have a few questions you can hopefully help me out with.
A: Thanks for that, and sure!
Q: We have 4 product lines and 2 of them are seasonal. i.e we have customers that year in year out purchase these items consistently but seasonally, for example, every spring and summer. Then they are dormant for Fall and Winter. Should I include these customers along with everyone else when doing an RFM segmentation?
A: Well, it kind of depends what you will using the RF(M) model for, what kinds of marketing programs will be activated by using the scores. If you know you have seasonal customers and their habit is to buy each year, AND you wish to aim retention or reactivation programs at them, I would be tempted to divide the customer base so that seasonal customers are their own segment. Then run two RF(M) models – one for the seasonals, and one for everyone else.
Q: If I include seasonal customers, and I run RFM say on a monthly basis, these seasonal customers will climb / fall drastically with time depending on the season, so it seems like it may complicate the scoring process.
A: Sure, and you could segment as I said above. Or, you could run across a longer time frame, say across 2 – 3 years worth of data. This would “normalize” the two segments into one and take account of the seasonality in the scoring – perhaps be more representative of the business model. However, the scores would become less sensitive due to the long time frame so the actions of customers less accurately predicted by the model.
Q: Can you provide me with some examples as to how segmentation is carried out? Let’s say I being with RFM and all my customers are rated 5-5, 5-4, 4-5 etc. What are the next steps, do we overlay with other characteristics like age, gender, etc? Or are the 5-3 etc. our actual segments?
A: This goes back to what you want to use the RF(M) model for. In the standard usage, each score will have roughly the same number of customers in it, those with higher scores will be more likely to respond to marketing and purchase, lower scores less likely.
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