RFM: From Acronym to Buzzword

Just when you’d caught up with the tide of acronyms rolling in, along comes one more: RFM. It stands for reach, frequency, and monetary. Like most online jargon, it’s not a new concept. It’s been around for 40 years. Though not widely understood, RFM is slowly coming above ground. For media buyers and sellers alike, it’s a concept worth considering (and it’s not rocket science).

According to www.whatis.com, RFM analysis is a marketing technique used to quantitatively determine the best customers by examining how recently a customer has purchased (recency), how often she purchases (frequency), and how much she spends (monetary). RFM analysis is based on the 80/20 Rule (or Pareto Principle): “Eighty percent of your business comes from 20 percent of your customers.”

Catalog marketers and direct mail folks have applied the method for 30 years or so. They capitalized on one simple principle: Those who made a purchase in the past are most likely to purchase again. Using RFM analysis, they rank prospects and customers on a scale of 1-5 (5 being the highest) for each parameter. Combined, the three scores make up an RFM “cell.” The information is typically stored and sorted within a database. Marketers search to find the best customers: a cell ranking of 555.

Let me guess, you understand the principle but never heard of it before? Most of us media or sales folk have read a book or two in regards to CRM. Perhaps it was Patricia Seybold’s “Customers.com.” Or maybe it was Seth Godin’s famous “Permission Marketing.” CRM uses the same principles as RFM.

Recently, my pal Tim McHale, CMO of Tribal DDB, interviewed Stuart Elliot of The New York Times. McHale mentioned CRM as a “hot buzzword” and asked Elliot what CRM means to him. Elliot replied that buzzwords are short term, CRM is long term. “That’s the reason why you should be thinking about the long term. All anybody’s talking about now is CRM, and the ‘C’ and the ‘R’ in ‘CRM’ [are], by definition, long term: talking about the long term, building a bond.”

According to Jim Novo, author of “Drilling Down,” marketers are generally concerned with three simple principles when using this approach:

  • Customers who purchased recently were more likely to buy again as opposed to customers who had not purchased in a while.
  • Customers who purchased frequently were more likely to buy again as opposed to customers who had made just one or two purchases.
  • Customers who had spent the most money in total were more likely to buy again. The most valuable customers tended to continue to become even more valuable.

RFM revolves around marketers’ Holy Grail: high response customers. RFM methodology ranks the current potential value of a customer in relation to the revenue a marketer can generate from that customer. At first glance, it seems like a simple concept to digest. Applying RFM migration analysis to an online advertising program is where it gets more complex.

We try our best to integrate email marketing campaigns, CRM, and offline media analysis with our online activities. Implementing RFM seems viable.

If you are considering an RFM analysis program, here are some quick tips and considerations:

  • As with any other CRM application, be careful and respectful in regards to a customers’ privacy — don’t spam customers (regardless of their ranking).
  • Do not neglect customers with low rankings.
  • As with any other list, cultivate prospects to increase rankings.
  • High RFM customers represent potential for revenue — not actual revenue.
  • Optimize creative and messaging based on RFM scores. For instance, if a customer has a low ranking, implement a strategy to garner decision making.
  • Focus on customer loyalty.
  • Effective RFM methods can potentially yield a high return on investment (ROI).
  • Do not abandon the lifetime value (LTV) of your customers (the net profit a customer is expected to contribute to your business over the time he remains a customer).

Old principle, new acronym. When implementing these (and other) practices in your current campaigns, remember: Think beyond the short term.

Editor’s Note: Ready to roll up your sleeves and crunch the numbers? ClickZ’s Analyzing Customer Data walks you through the math in an in-depth three-part series on calculating RFM.

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