Category Archives: Customer Experience

New RFM: Customer Retention in “Subscription” Businesses

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

How do you measure likelihood of customer defection when purchase behavior is highly orchestrated or executed due to repetitive billings? Yea, it’s a bit more complicated because “orders” really can’t express any kind of behavioral change, can they? So, you have to find indicators other than sales to provide the triggers. The Drillin’ the Drillin’ …


Q:  Jim, first let me say that I am enjoying your book VERY MUCH!!  Nicely done, and a nice job of integrating it with the CRM paradigm, 1-to-1 etc… I’m reading very slowly and finished the Latency Metric Toolkit.

A:  Great!  Thanks for the kind words.

Q:  I had a couple of questions on the Latency toolkit and the Latency tripwire, especially as it applies to environments with built in cycles for repeat purchases.

I am in a business where our resources are quarterly based, i.e. customers purchase our resource use them for a quarter and re-purchase the next quarter’s resource.  That is, we have a built in pattern, where customers would purchase our resources each quarter.  I was wondering how well I can use Latency with this type of built in cycle or if I would have any problems applying your Latency concepts to it, maybe they apply that much more readily?   In our case we try to call most folks who haven’t purchased within 2 weeks of a new quarter beginning.

A:  Right, a subscription-type business.  This is also an issue with utilities and other like businesses who bill about the same amount each month or have contracts for service (like wireless).  The answer is if the revenue generation really doesn’t represent anything to do with the behavior, then you simply look for other parameters to profile.  For example, a friend of mine was responsible for analyzing the likelihood of subscription renewal in a business that provided the content online.   Increasing Latency of visit was a warning flag for pending defection, and they triggered their most profitable campaigns based on last visit Recency.  In wireless, the correlations are found in payment Latency and age of phone.

Continue reading New RFM: Customer Retention in “Subscription” Businesses

New RFM: Using RF or RM Instead of RFM

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Sometimes the traditional RFM model does not work very well for a specific business model. For example, small business databases can be too small to fill out all 125 RFM segments properly, resuslting in distortions of predictive capability. Optimizing the traditional RFM approach for unique business model criteria is a very useful skill, and it’s actually not difficult if you understand the levers of the business model. To Drill or not to Drill, that is the question …


Q:  I’ve used your site a lot and found it to be very informative.

A: Thanks for the kind words!

Q:  I have a question about the use of RFM analysis for a low margin, eCommerce business.  I read that for a relatively small customer list (<50k) using just the “RF” of the RFM analysis would be preferred since the “M” tends to hide shifts in behavior.

A:  Well, the M tends to smooth shifts regardless of the size of your list.  In addition, if you have a small list, 125 segments is too many to be really useful, so RF at 25 segments in more intuitive.  The real issue with M or Monetary Value is up and coming, accelerating customers.  If you use total spend (M), it will “punish” them with a lower rank.  But the fact is they have more future potential because Recency is low and Frequency is ramping.  Inversely, M tends to reward customers who have spent a lot in the past with a higher rank, though they may actually be declining or defected customers.  Predicting the future is more profitable than reporting on the past, so given a choice, I would drop “M.”  This is especially true on the web, where communication costs are low and changes in behavior can be very rapid.

Q:  My question to you is, since I’m talking about a low margin business, wouldn’t “M” actually be more valuable than “F” for the analysis?  For example, if 40% of my customers are driving 70% of my sales and 100% of my profits, that says that 60% of my customer base is losing me money.  I don’t want them to be given a higher value rating because they’re placing MORE unprofitable orders than someone placing fewer but profitable orders.  You see what I’m saying???

Continue reading New RFM: Using RF or RM Instead of RFM

Are Quitters of Club Likely Still Good Customers?

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

How do you handle the measurement of “likely to purchase” when there’s a built in cycle of purchase as a “member”, like in a book club or other auto-delivery scheme? And what if a member quits membership but keeps buying, what does that mean for predicting future buyer behavior? Oh, the complexity of it all! Let’s do the Drillin’ …


Q:  I just ordered the book too, so I am eager to learn more about SIMPLE ways to implement RFM-based strategies.

A:  Well, thank you for ordering!  I hope it fulfills your expectations.

Q:  In the continuity club (Jim’s Note: flower of the month, book of the month, beer of the month) club business though, a little of the RFM process looks tricky because everyone has a certain Frequency built-in, because of the “repeat” nature of clubs.  Also, we’re starting to see a  phenomenon where customers that drop out of our club continue to order from us.

A:  This is quite normal, depending on how the club is set up and whether or not you make it “easy” for people to continue.  In some clubs, you are either in or not (books, CD’s, credit cards).  Most catalog-type clubs (pay a fee in exchange for ongoing discounts / added services) see continuation beyond club membership.  It’s a volume-based thing and a “rational” decision by the consumer – if you need to buy a lot of stuff, joining the club makes sense, because the discount pays for the membership.  

In your case, it might be more attached to education, for example – you join the club to educate yourself about the products, then quit when you can “do it on your own.”  Or, you get lots of  product to experience the variety, and settle into a specific usage pattern.  This is the Customer LifeCycle at work.  If you can recognize these patterns, you can use them to predict what customers are likely to do next.  If you can predict behavior, you can create very high ROI customer marketing programs.

Continue reading Are Quitters of Club Likely Still Good Customers?