There's a predictive modeling and segmentation technique that can dramatically improve email click-throughs and conversions. It's called RFM, and direct marketers have been using it for years to identify their best customers and send them special, tailored offers. Learn how it works and start applying it to your email campaigns.

RFM: a Proven Behavioral Marketing Segmentation Technique

RFM stands for Recency (when the customer placed the last order), Frequency (how many orders the customer placed in a period of time) and Monetary (how much money the customer spent). It relies on the premise that someone who recently bought something, who shopped often and who spent a lot is more likely to respond to your next campaign than someone who bought something a long time ago, shopped infrequently and spent next to nothing.

Coupled with customer lifetime value analysis, RFM enables organizations to significantly increase response rates by sending offers only to the subset that is most likely to buy. In the direct-mail world, where every name comes with set production and shipping costs, there's a strong motivation to pare lists down. As a result, direct marketers have used RFM for decades.

In email marketing, we haven't been quite as motivated because of two common misconceptions:

• Myth #1: Email is cheap, so there's no downside to blasting the message to everyone. There's actually a pretty big downside: list fatigue. Over time, as recipients receive multiple messages they don't find relevant, they become less and less likely to respond, and more and more likely to report your messages as spam.
  
  This in turn, lowers your sender-reputation score, the most important factor ISPs use in determining whether to filter your message to the junk folder instead of the inbox. The end result? A damaged brand ("Just what I need, another email from that company") and deliverability issues that can prevent engaged recipients from receiving your messages.
  
  
• Myth #2: You get a bigger response rate if you send to a bigger list. It seems logical, but it is just not true. Sending to an additional number of warm bodies does not necessarily generate higher click-throughs. In fact, it can actually produce higher spam complaints. You are much more likely to increase response rates when you send relevant, targeted messages to smaller subsets of your lists.

How to Apply RFM Segmentation to Email Lists

Email marketing allows you to measure customer interaction and engagement in many more ways than direct mailing could ever do. Depending on your email database and marketing strategy, other metrics can be used in place of the traditional RFM parameters, giving you many different ways to perform RFM analysis:

Once you've decided which metrics make the most sense for your business, you'll need to tie your email database to the system that contains purchase or conversion history, such as your CRM or Web-analytics tool.

Now you are ready to perform RFM segmentation.

Because RFM has been a direct-marketing staple for so many years, many popular data-mining and statistical analysis tools generate ready-made RFM-classification reports. However, if you don't use statistical analysis tools, fear not. Unlike other predictive-modeling techniques, RFM is based on past customer behavior and does not require heavy statistics-driven analysis.

One way to perform RFM segmentation is to simply sort your list for recency, in order of highest to lowest. You then divide the list into five equal segments, giving the top 20 percent a recency score of 5, the next 20 percent a score of 4 and so on. Each recency segment is then sorted for frequency and divided into five equal segments, resulting in 25 recency plus frequency segments. Each of these segments is then sorted for monetary and divided into five equal segments, leaving you with 125 segments that have RFM scores ranging from 555 to 111. This is your RFM index.

One popular method for deriving an RFM index from your database. (Source: Quick Profits With RFM Analysis by Arthur Middleton Hughes)

Of course, depending on the size of your database, you could divide it into deciles or other n-tiles, instead of quintiles. Or if you are very familiar with your database, you could simply use intuitive groupings, such as "purchased in last month, last three months, last six months or greater than six months," as the basis for your RFM classifications.

As you can see, RFM is very adaptable, and with some experimentation, you will be able to obtain dramatic lift gains.

Sending Different Types of Email Campaigns to Different RFM Segments

Once you've assigned all of the records in your database a specific RFM classification, you run a test campaign, typically on 10 percent of your list, to determine which RFM groups to mail to.

In traditional direct mail, you perform a break-even analysis to determine which mailing recipients are profitable. You look at the test-group response rate for each RFM cell, and then stop mailing to cells whose response rates are less than the rate required to break even on mailing costs.

In email, however, the goal is not to simply stop mailing to your weakest segments, it's to find the right tactics that resonate with and re-engage lower-scoring recipients, too. So you can test different types of messages to see which RFM segments respond best to which types of campaigns, and stop sending those particular campaign types to segments that fail the breakeven test.

Or, instead of using the breakeven metric, you could simply compare the conversion rates of different RFM segments and send future campaigns only to the groups who convert the best.

Here are some ideas for the types of campaigns that may work best with different RFM segments:

• High Recency, High Frequency and High Monetary: Reward your most loyal customers and prospects with exclusive email privileges that make them feel special. For example, some retailers automatically offer free shipping and other perks to their best online customers.


• High Recency, Low Frequency and Low Monetary: This segment includes your newest customers or subscribers. Give them a good first impression of your company with welcome offers, product-usage tips or other information that newbies would find helpful.


• Low Recency, Low Frequency and Low Monetary: As in direct marketing, your least-engaged recipients simply may not be worth mailing to. But in email marketing, they may be great candidates for a re-opt-in campaign. Double-check whether they still want to hear from you, and remove them from your list if they don't.

Use RFM to Send Better Messages to Your Best Email Recipients

RFM segmentation is a relatively simple way to break down your email list based on recipients' past behaviors. Let it lift you out of the ineffective realm of batch-and-blast, and into a whole new world of targeted email with conversion rates that soar. Trust a Lyris email expert to do the RFM analysis for you and advise you on email-segmentation best practices.

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About the Author

Emily Chen is a senior integrated marketing consultant for Lyris. She uses a data-driven approach and industry best practices to help clients optimize all aspects of their e-marketing programs, from contact strategy to creative design to marketing analytics.

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