Recently a Repeat Customer Insights was asking about what triggers the RFM scores to change, like from Recency 5 to 4.
There are no set points or triggers that move customers from one RFM score to another.
Rather, RFM ranks each customer against your customer base as a whole and based on where the individual falls, that’s their score.
For example, if a customer’s reorders are more frequent than 85% of the other customers then their Frequency score would be 5 (the Frequency score for the top 80-100%).
That means if you have an event that changes customer behavior (e.g. big sale) those customers who bought will have their ranks improved relative to the customers who didn’t buy. If their percentile rank shifts enough, they could end up with a different score and new segments.
That’s the automatic self-balancing part of the model and why it works equally well for stores with 5,000 customers as stores with 1,000,000 customers.
RFM is just one of the models Repeat Customer Insights uses with its customer and order analysis. It comes with a 14-day free trial so you can see how it works and get some ideas right away.
Use cohorts to find out who the best customers are in your Shopify store
Repeat Customer Insights will automatically group your customers into cohorts based on when they first purchased. This will let you see how the date customers bought would impact their behavior.