Navigating the vast sea of customer data can feel like a treasure hunt without a map. But what if we could give you just that, pointing you to your different customer segments?
RFM segmentation is a powerful method for classifying customers by assessing three key factors that determine their quality. RetentionX does the analysis for you and provides you with initial segment recommendations; however, you can also use the analysis as a basis to create your own RFM segments!
Pre-Defined RFM Statuses
The RFM Analysis assigns Recency, Frequency, and Monetary Value scores to each of your customers. This results in up to 64 distinct RFM score combinations (4x4x4). To make the results of the analysis as easy to use as possible, RetentionX pre-identifies six customer groups and assigns an RFM status to them. For example, your Top Customers consist of all customers who are assigned an RFM score of 111, which means that they purchased recent, do so often, and spend more than other customers.
Although all of your customers are assigned an RFM score, not all of them belong to one of our pre-defined RFM statuses. This ensures that you can easily focus on the right groups of customers. Learn more about our pre-defined RFM statuses here.
Custom RFM Segments
You have two options to create custom RFM segments:
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Based on RFM Statuses
You can easily combine multiple RFM segments into a single segment. For example, let's say you want to use RFM analysis to identify a seed audience of your best customers so you can create a lookalike audience to attract future Top Customers. Meta, for example, requires that this seed audience be larger than 1,000 users. If you don't have enough Top Customers, you can combine your Top Customers, High Potentials, and Loyal Customers to achieve the required sample size, while still maintaining control over customer quality and using only the best customers based on their recency, frequency, and monetary value behavior. Such a segment would look like this:
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Based on RFM Scores
Consider a scenario where you sell, say, dog food. Imagine two customers who both make regular monthly purchases that are in the top 25% for recency and frequency compared to your overall customer base. One customer, who owns a large dog, spends significantly more on dog food each month than the other customer, who owns a small dog-because the large dog simply requires more food.
As a result, the customer with the large dog is categorized as a Top Customer due to the higher revenue contribution, while the small dog owner's lower spend results in a lower monetary value score, classifying them as a Small Buyer. Now, if you wanted to identify all the customers who are top performers in terms of recency and frequency, but only exclude the worst 25% in terms of monetary value - to promote your loyalty program, for example - you could create a customer segment that looks like this:
Once your segments are created, you can generate audiences based on them or analyze behavioral patterns by applying the segment to any report.
Read our full blog post about RFM analysis for Shopify stores here.
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