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Customer Retention. Automated

The Ins & Outs of RFM Analysis

Posted by Polly Flinch on Sep 18, 2015 4:07:09 PM
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RFM Analysis is a proven marketing technique that has traditionally been used by catalogers (old school marketers) to increase conversion rates and reduce the cost of mailing catalogs. Now the Golden Age of the catalog may be behind us, but digital marketers can learn a thing or two from marketers of the past, by using RFM analysis to increase conversion rates, personalization, relevancy, and ultimately revenue and user experience. Think of it this way, do you know who your best customers are? What about your churning customers? What about your customers who spend a lot, but only purchase once in a while? If you’ve answered no to any of the above questions, this article may help you.

RFM Explained

The goal of RFM analysis is to segment your customers cased on buying behaviors by looking at three values: 

  1. Recency (the number of days since the customer’s last purchase)
  2. Frequency (the number of orders placed in a given time period)
  3. Monetary (the total amount of money spent by the customer over a given time period)

The goal of RFM Analysis is to quickly identify and sort customers on the above criteria with the intent of creating targeted, personalized marketing campaigns for each cohort. This is particularly useful as we head into the holidays. Use the steps below to pull your holiday shoppers from 2014 and re-target them again for the coming season.

RFM Analysis in 4 Simple Steps

  1. Export a list of all of your customers during a certain time period, let’s use 10/01/2014 - 12/31/2014 for this example. Make sure this file includes the date of the most recent order, the number of orders placed during the selected time period, the total value of all purchases made during the selected time period, and customer ID. NOTE: If you can include the customer’s email address, this will save you time later on, so make sure to export this as well.
  2. Sort all customers in the spreadsheet in ascending order based on Recency.
  3. Split the customer list into quartiles and assign each customer a number, 1-4, depending on which quartile they fall into. Quartile 1 will have a rank of 1, quartile 2 will have a rank of 2, and so on.
  4. Repeat steps 2 and 3 for Frequency and Monetary Value.


Now that each of your customers has a score of 1-4 for each of the 3 factors, you can start segmenting your list. Here’s a cheat sheet of the top 5 segments for your records:


Best Customer      R1F1M1
Lost Customer / Churned Customer     R4F1M1
Almost Lost Customer / Disengaged Customer     R3F1M1
Loyal Customers (anyone who purchases at a high frequency)     F1
Big Spenders (They may not purchase often, but they spend a lot. This a chohort you will want to target to turn into loyal shoppers.)     M1
Each cohort identified above needs to be handled in a different manner. Remember, not all customers are created equal. Download the RFM Analysis guide to learn more and get access to more RFM segments.



Topics: Customer Retention, Best Practices

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