A lot of power comes from combining things.
Peanut butter and jelly.
Hot peppers and vinegar.
Bart and Homer.
That combining is what make RFM a powerful customer analysis model. By combining three different measurements it can cover a lot of different behavior while still being simple to understand.
(Unlike most AI or “fake-AI” systems that are too complicated for even their developers to explain).
Having three measurements also gives you a lot of other options for segmenting customers.
- RF will show who the active customers are.
- RM will show how customer activity compares to their lifetime spending.
- FM will show ordering sizes.
You get all of that information, in addition to the regular RFM segmenting just from doing a single analysis.
Analyzing your Shopify customers and calculating the scores can be time consuming though. It’s easy to understand but once you get more than a few hundred customers it’ll take too long to do it by hand.
But not for a computer algorithm.
Repeat Customer Insights can calculate the RFM scores for your Shopify store automatically. It refreshes them automatically regularly which is vital to get the correct results.
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.