eCommerce Analytics

I recently had the opportunity to sit down with one of the marketing professors at MIT’s Sloan School of Management to discuss the current state of marketing analytics. One of the many topics that came up during our discussion was why so many companies are still basing their marketing strategy on RFM. For those of you unfamiliar with the term, RFM stands for recency, frequency and monetary value. It has been used in direct marketing for the last 30 years and continues to be the basis of many “rule” based email and direct mail campaigns. Why? Well, for starters, it’s easy for many marketers to understand: customers who bought recently and have a history of buying large amounts often are more likely to purchase again in the future. Unfortunately, RFM fails to consider many of the factors necessary to truly evaluate the profitable of any one customer - mainly, the cost of acquisition and the cost of customer service and retention.

Does it matter? Absolutely. Way back in 2003, Rajkumar Venkatesan and V. Kumar published a paper highlighting the benefits of using CLV over RFM. They showed that the net profits from the top 5% of CLV-ranked customers were 1.6 times the net profits of the top 5% of RFMers. Additionally, they found that using CLV to better target customers increased profits by almost 67%.

So with increases like that, why are so many companies still using RFM? Well, to be honest, most companies still don’t know any better. However, as the global community gets more competitive, savvy marketers are beginning to look past RFM to make better use of their data through more advanced data analytics. And the good news is that the field of marketing analytics continues to provide us with better ways to analyze data every year. While CLV continues to be one of the best ways to target customers, research by professors like Pete Fader at Wharton and Dipak Jain at Kellogg have given us models that more accurately forecast number of purchases and retention rates of customers for non-contractual businesses. Recent papers have also focused on enhanced forecasting of the migration of customers from direct mail marketing to email blasts (check out Customer Channel Migration by Ansari, Mela, and Neslin).

With the rising cost of direct mail and the waning interest of customers through email blasting, it is clearly the time to improve the effectiveness of marketing to improve the overall profitability of the business. While I’ll admit that RFM was a great marketing tool in the past, there have been so many advances in marketing analytics since then that it’s time to move on.