Ordering frequency is another predictor of customer loyalty.
RFM measures this with the middle component, Frequency. That means customers with a score of 4 or 5 there are more likely to be loyal but there's another method I also include in Repeat Customer Insights.
First, find out your Average Orders per Customer. This will show you how many times an average customer is ordering before they stop.
Next, decide on a multiplier for loyal customers. I use 2x, meaning if a customer orders double the average then they are loyal.
Finally, run through your Shopify customers and find everyone who has placed at least that many orders.
These customers were potentially loyal, that doesn't mean they are loyal.
You'll want to do a bit more analysis to make sure they are still active and still buying. That's where the RFM method of loyalty has a leg-up on this. The other two components of RFM handle other aspects of the customer to make sure they are active and placing good-sized orders.
Comparing how often a customer orders against the average is a simple way to get an idea of who might be loyal. It's also great for building a loyalty program around, especially order-frequency based ones.
This analysis is done for you in the new Who Are Loyal focus page in Repeat Customer Insights.
Eric Davis
Learn what your customers are actually doing instead of just guessing
One of the best ways to build a sustainable business starts by getting your customers to come back. Mastering that simple process can be difficult, but builds a lifelong business.
Repeat Customer Insights can help you understand your customer's behavior. With its collection of behavior reports, you can see what they're actually doing instead of guessing and having your efforts fall flat.