The RFM model works really well for large stores. With 125 unique segments, there's a lot of fine-tuning potential.
For smaller stores (and stores that don't want to fiddle), it might be too much as it is.
Say you get 500 orders per month (6,000 per year). That means you'll have about 4 customers added per segment each month. Not enough to market to.
That's why Repeat Customer Insights builds on top of RFM with the Automatic Segments and Customer Grades.
Automatic Segments is about 30 different segments and Customer Grades is 5.
For that example store, that means there'll be about 16 customers added to each Automatic Segment and 100 added to each Customer Grade. Much better sizes for building campaigns around. Even enough to experiment with control groups.
Both use the underlying RFM model so they share the benefits from it automatically. Automatic Segments merges and combines similar RFM segments while Customer Grades adds a scoring algorithm to RFM to rank customers.
Also as your store grows, it's easy to grow into another model.
Get a complete view of your customer behavior
The cohort analysis in Repeat Customer Insights will automatically build cohorts for all of your customers. It has the ability to go back through your entire store history so you can get a complete view of your customer behavior.