RFM is a common heuristic used to measure customer value. The abbreviation ‘RFM’ stands for ‘recency,’ ‘frequency,’ and ‘monetary value.’ Given the common business knowledge that most of a firm’s business comes from a relatively small number of clients (e.g. the 80/20 rule or the Pareto Principle), it is very much in your firm’s interests to identify those customers and to spend one’s marketing budget more economically. Using the CrossEngage platform, you can segment your users by RFM value, even if you don’t have a dedicated Business Intelligence analytics software!
The following document describes how customer segmentation in CrossEngage can be used to group those customers with the highest (or lowest) value. Whereas the highest value customers ought to be targeted with marketing communications to continue developing a meaningful relationship with your brand, you may consider deleting low value customers from your database entirely (see our Bulk User Management documentation). For more information on targeting messages to segments based on RFM, see the following: https://www.barilliance.com/rfm-analysis/
To set up a segment, first select “User segments” from the navigation bar.
Select “Create new segment”
Give your segment a clear, descriptive name
Remember that RFM stands for ‘recency,’ ‘frequency,’ and ‘monetary value.’ In this example we demonstrate the creation of a segment composed of high RFM customers. Thus, the segment conditions must select for customers who have purchased recently, frequently, and with high monetary value. The particular values which these conditions must meet are to be determined by the nature of your firm.
Click ‘Add Conditions.’
Next, add three conditions
Recency is crucial because the longer it takes for a customer to return, the less likely he or she is to return at all.
The crucial aspect of this segment condition is the ‘Timespan.’ This condition collects customers who have ordered an item within a week of a campaign’s dispatch.
Frequency is also important; it measures the ‘intensity’ of a customer’s relationship with your business.
This condition collects users who have purchased 5 items in the previous 25 months (the maximum amount of data that can be retained).
Tracking the monetary value of previous purchases allows you to distinguish between heavy and light spenders, with heavy spenders being preferred.
This condition uses a property to collect users who have made a purchase with a value greater than 500€.
This segment is now complete. As stated above, the specific values of the various conditions must be determined with respect to your particular company and industry (i.e. recency and frequency must be scaled relative to the average frequency of purchase in your industry, while monetary value must be scaled relative to average prices). Nonetheless, this segment can be used to target your highest value customers, thus providing you with a simple and efficient way to maximize the ‘bang for your buck.’ Alternately, this method can be reversed to group your least valuable customers so that they can be deleted from your user base.