Digging into RFM segmenting in Shopify

Last time I introduced you to the RFM analysis as a way to combine three simple segments into one powerful segment.

Now you're going to learn what happens when you're able to perform an RFM analysis on your customers.

You've already seen how to combine the Recency and Frequency segments but a full RFM analysis is more than just looking for the highest/lowest customers in each.

A good way to think about the RFM analysis is that you're grading your customers on the three segments, which in turn creates a three-dimensional segment like this:


The best customers are in the larger, shaded squares and they represent customers who have ordered from you most recently, most frequently, and have spent the most with you.

The smaller squares out near the edges of the lines represent customers who aren't performing as well in one, two, or three areas.

Depending on the purpose and what you want to do with your segments, you can combine them in different ways. For example:

The problem with RFM analysis and segmenting in general is that it can become overwhelming because they produce so much data for you.

To counter this I recommend focusing on two or three high of your best segments (the 20% who provide 80% of the value) and ignoring the rest. By optimizing your best segments, you might find your your weaker segments improve too.

Now actually performing the RFM analysis is a bit tricky. Even with only a few customers and orders, you still have a lot of math to do every time you make a sale.

That's why I developed Repeat Customer Insights. I wanted to do the RFM analysis automatically for you.

To get started, use the link above to start your free trial and start to optimize store for revenue growth.

Eric Davis

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Customer behavior analysis for better Shopify store performance

The Shopify App that increases repeat customer purchases through customer behavior analysis.

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Topics: Analytics

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