The RFM tab gives a comprehensive overview of your transaction history broken down into three separate categories: Recency, Frequency, and Monetary Value.
There are a few key points about when to use your RFM data: Recency is useful for gauging for active your customer base is; Frequency shows how often your customers are spending; and Monetary Value helps you determine your average customer value.
The Recency feature displays both how many new customers you acquired and how many others made their latest purchase on a monthly basis, starting from the current month, and going as far back as the last 60 months.
The Frequency tab breaks down how many times your customers make purchases. It gives you insight into the distribution of 1x buyers and multi-time buyers in your database.
This is a great way to measure customer value. Since each group is mutually exclusive, you can measure your percentage of one-time buyers compared to repeat, loyal customers. If your total percent of 1x buyers is greater than 55%, it is very likely you have a one-time-buyer problem - and that you should start countermeasures immediately.
The Monetary Value feature allows you to analyze the amount of money your customers have spent with your company over their lifetime. This is shown in the form of dollar amount per customer and is broken down into a list of price ranges.
The greater the monetary value, the more that customer has spent with your brand over their lifetime - making them an enticing target for exclusive appreciation events and lookalike models.
Configuring Your RFM Report
You can change the ranges the monetary value and frequency reports use to group your customer base.
You can select the number of orders to see your results grouped by, as well as the monetary ranges for each list.
Here is a quick recap of how each tool can help gain a better understanding of your customer base:
Recency is useful for gauging for active your customer base is.
Frequency shows how often your customers are spending.
Monetary Value helps you determine your average customer value.