I was reading an article by Shopify about using email marketing, lifecycle automation, and RFM.
There's a lot of good information in it except they slightly missed the mark with RFM:
Recency is the number of days since a subscriber’s or customer’s last purchase. An R0 purchased today. An R365 purchased a year ago.
Frequency is the total number of times a subscriber or customer has purchased. An F0 has never ordered. An F10 has ordered 10 times.
Monetary value is a customer’s total spend—the sum of all orders.
Using their scoring method you'll end up with customers like this:
- "187", 4, "$234.56"
- "1", 2, "$87.12"
- "145", 7, "$117.56"
While useful to see the data behind the scenes, that misses much of the power of RFM:
The ability of RFM to relate your customers against themselves
If they used the standard RFM definition, you'd see something like this:
- 3, 4, 5
- 5, 2, 3
- 3, 5, 1
Now bring in the RFM scorecard (which is always consistent from business to business) and you get a story for each customer and your customer base as a whole.
- Average ordering time, probably going to order soon. Strong repeat customer. Very high spender. VIP?
- Just ordered. New repeat customer. Average spending. Average customer.
- Average ordering time, probably going to order soon. Strong repeat customer. Very low spender. Discount buyer?
A customer segmentation system that is consistent and standardized like RFM is much easier to operate than a system that requires you to think and evaluate your segments every time you use it. And using a tool like Repeat Customer Insights can make it effortless to build the segments.
Which marketing strategies are producing the best customers for your store?
Analyzing your customers, orders, and products with Repeat Customer Insights can help find which marketing strategies attracted the best customers over the long-term.