A simple way to evaluate customers is to compare them to your hypothetical average customer.
Has this customer ordered more or less often than the average customer?
Does this customer spend more or less in each order than the average customer?
Does this customer order sooner or later than the average customer?
These sorts of questions can act as a simple filter for creating customer segments. You'll have two segments per comparison:
- a group better than (or equal to) the average customer
- a group worse than the average customer
Some comparisons might be similar and correlate (e.g. ordered more often and spends more in each other) but not always (e.g. ordered more often but spends less each time). Combining those comparisons can quickly give you a lot of customer segments to work with.
The RFM model uses only three comparisons but there are five levels of answers for each. Basically: lot more, little more, about the same, little less, lot less. Combining those three comparisons give you 125 unique segments, more than most Shopify stores need.
RFM is powerful and easy to understand. Which is why RFM is one of the main models used while customer segmenting in Repeat Customer Insights.
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