Kenan-Flagler Business School The University of North Carolina
Recency, Frequency and Monetary (RFM) Analysis
RFM is widely used by direct marketers of all types for selecting which customers to target offers to. The fundamental premise underlying RFM analysis is that customers who have purchased recently, have made more purchases and have made larger purchases are more likely to respond to your offering than other customers who have purchased less recently, less often and in smaller amounts. RFM analysis can also be used to target special offers to ‘welcome’ new customers, encourage small purchasers to spend more, to reactivate lapsed customers, or encourage other marketing initiatives. RFM analysis uses information about customers’ past behavior that is easily tracked and readily available. Recency is how long ago the customer last made a purchase. Frequency is how many purchases the customer has made (sometimes within a specified time period, such as average number of purchases per year). Monetary is total dollars spent by the customer (again, sometimes within a specified time period). RFM by Example: The BookBinders Book Club The BookBinders Book Club sells specialty books and selected other merchandise through direct marketing. New members are acquired by advertising in specialty magazines, newspapers and TV. After joining, members receive regular mailings offering new titles and, occasionally, related merchandise. Right from its start, BookBinders made a strategic decision to build and maintain a detailed database about its club members containing all the relevant information about their customers. Initially, BookBinders mailed each offer to all its members. However, as BookBinders has grown, the cost of mailing offers to the full customer list has grown as well. In an effort to improve profitability and the return on his marketing dollars, Stan Lawton, BookBinders marketing director, was eager to assess the effectiveness of database marketing techniques. Because of direct marketers’ long history of success with RFM and its relative ease of use compared with more sophisticated modeling approaches, Stan decided to test the RFM approach.
Professor Charlotte Mason prepared this note to provide material for class discussion rather than to illustrate either effective or ineffective handling of a business situation.
Copyright 2003 by Charlotte Mason.
Page 2 Stan proposes to conduct live market tests, involving a random sample of customers from the database, for new book titles in order to analyze customers' response and calibrate a response model for the new book offering. The response model's results will then be used to "score" the remaining customers (i.e. those not selected for the test) and to select which customers to mail the offer to. BookBinders’ customer database provides a complete record of purchasing history for each customer. This includes how long they have been a customer, the specific titles ordered and summary totals by category such as cooking or children’s books. Of direct relevance for RFM analysis, BookBinders keeps a record of the number of months since last purchase, the total number of purchases made as well as the total dollars spent by each customer. With these three pieces of information for each customer, Stan can easily test the RFM approach. The Art History of Florence Offer To test the RFM approach, Stan conducted a test. He had a random sample of 50,000 customers drawn from BookBinders customer database. By selecting a random sample of customers, Stan could be confident that all types of customers would be represented: both recent and not-so-recent purchasers, frequent and infrequent purchasers and customers spanning a range of total dollars spent. This random sample of customers was mailed an offer to purchase The Art History of Florence and their response – either purchase or no purchase – was recorded. Now for each customer in the test, Stan knew his or her values for the...
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