A Repeat Customer Insights customer was asking about how the RFM model adapts to changes in the products offered as the store moves to more subscriptions:
So all of these [RFM scores] are relative to each other based on the ratings into 20% categories.
Does this mean that if we aim to extend our AOV and increase retention with subscription programs the model will automatically stretch the groups including whales as our AOV moves?
Yes. RFM doesn't use AOV but it uses the total spent by the customer which is better in this case (M is Monetary, aka total spent).
What'll happen with a subscription program is that each renewal will increase Recency (they just renewed today), Frequency (they ordered one more time), and Monetary (they have spent more).
Eventually the best subscribers will rise to the top scores and will show up in the better segments.
This will also push down customers with weaker signals (one-time, low total spent, etc).
Eventually as your best customers behave differently than your weaker ones, the spread in each group will be wider. e.g. a segment defined as $200 through $20 changing into a segment defined by $400 through $20.
This is one way RFM becomes self-adjusting as your store and customer behavior changes.
If you haven't installed Repeat Customer Insights yet, it's an easy way to get a detailed look at your customer behavior using RFM, cohort analysis, other algorithms.
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.