Category Archives: Digital Analytics

RFM and Customer LifeCycles

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Today we’ve got a bit of confusion between RFM and Customer Lifecycles, but that’s a situation we’ve been dealing with for 30 years so not really an issue. Sure, it can be confusing. Reality is, these two ideas are related in some ways but not remotely the same in other ways. Plus, each is very good at accomplishing the job it was designed to do – as long as the user understands the problem to be solved and the specific purpose / output of each approach.

So, you want to understand these ideas better? OK, get ready for the Drillin’ …

Q:  I have a small sampling of the RFM scores that correspond to the various lifecycle stages.  For instance, 111 & 112 correspond to the acquisition stage, 333 & 443 to the growth stage, etc.  However, I’m looking for a complete listing of all 125 possible RFM scores and their corresponding lifecycle stages.

Can you please send this my way?

A: Wow, I certainly hope you didn’t get this idea from me; if you did, I have done a terrible job of explaining something somewhere. I would be very interested in the source of this idea, that a LifeCycle stage can correspond to a single RFM code or score.

An RFM code or score is the ranking of a single customer against all other customers for likelihood to respond and future value at a specific point in time. High scores equal high future value; low scores equal low future value.

A single RFM score represents this ranking at a fixed point in time – the day the scores were created. There is no “cycle,” which implies “over time,” inherent in an RFM code. Only if you knew the previous RFM code or sequence of codes could you imply a “LifeCycle stage”. This is, of course, what my book is about – using a modified version of RFM to track and profitably act on customer LifeCycle behavior. If you know the LifeCycle, you can predict behavior. If you can predict behavior, you can dramatically improve marketing ROI.

If a customer is a 333, you don’t know if they are falling or growing into it. They could be coming from above it – falling in value, or coming from below it – rising in value. For example, most new customers start at a 51x – they have to, because by definition, they are “new” (R = 5) but have bought once (F = 1). But this same customer 3 months from now might be a 555 or a 222 – either ramping up or sliding into oblivion. If you don’t know what their score used to be, you can’t imply anything about a “cycle” or any “stage” in the relationship with the customer.

That said, customers in the 111 and 112 are typically old, defected customers – not new or “acquisition stage” customers as you called them. All customers start in the high numbers and work their way down into the low numbers throughout their lifecycle. The question is how long will it take to get from high to low, and can you do anything to slow this process or stop it. The scores tell you if what you are doing is working, and how to drive profitability following the two fundamental rules of High ROI Customer Marketing:

  1. Don’t spend until you have to
  2. When you spend, spend at the point of
    maximum impact

If you are looking for some generalized system, I wouldn’t worry about the detail of 125 RFM codes, there is really no meaning there unless you have millions of customers. The most important variable, from a LifeCycle perspective, is usually Recency, so you could roughly categorize the LifeCycle of customer into 5 blocks using the R score. The second two variables, F and M, are not so much about the lifecycle of the customer, but the value of the customer now and in the case of F (sometimes), future value. Any customer with a low R value but high “FM” value was a very valuable customer that isn’t a customer anymore. In terms of Lifecycle, they are at the end. In terms of value, they are at the top.

For more on actually putting these ideas on measuring and tracking Customer LifeCycle into practice, check out these series, in order of perhaps the most logical way to learn the concepts:

Customer Defection Rejection

Trip Wire Marketing

Measuring Engagement

and for a higher level / deeper structure / management view, see here:

Framework for Engagement

Jim

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Free / Pay Web Site Optimization

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Today we’ve got a bit of confusion between RFM and Customer Lifecycles, but that’s a situation we’ve been dealing with for 30 years so not really an issue. Sure, it can be confusing. Reality is, these two ideas are related in some ways but not remotely the same in other ways. Plus, each is very good at accomplishing the job it was designed to do – as long as the user understands the problem to be solved and the specific purpose / output of each approach.

So, you want to understand these ideas better? OK, get ready for the Drillin’ …

How do we make money on a content site? Free? Pay? Some combination of both? There’s been a lot of guessing and testing by the big media guys on how to work this, but how do the the small segments / little guys make this work, what can be measured to help? What about newer platforms like Substack, how do you measure optimization? On with the Drillin’ …

Jim’s Note: If you don’t know what Recency and Frequency are they are explained here, and RFM is covered here.  “Intensity” is Views per Session, in this case a “proxy” for visitor value.

Q: Hi Jim,

Should we use:

RFI – Recency, Frequency, Intensity
RFM – Recency, Frequency, and Monetary
or
RF – Recency, Frequency

to measure visitor value, and what should these terms ideally mean?  Total Sessions, Total page views, etc.  Also, when you measure Frequency, do you only include the Frequency during a specific period of time (i.e. one month, or one week), or do you include total lifetime activity per user?

A: On the advertising side of the business, I think the page views/session stat is probably the best to use.  The reality of the ad-based business is it doesn’t matter if they come back, you are selling impressions, not people.  I don’t think you have to overcomplicate it with formulas like RF or RFM, because you are primarily dealing with audiences, not individuals.  RF and RFM are about predicting if individuals will come back.

Continue reading Free / Pay Web Site Optimization


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Choosing Customer Retention Metrics for the Supplements Business

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Today we’ve got a bit of confusion between RFM and Customer Lifecycles, but that’s a situation we’ve been dealing with for 30 years so not really an issue. Sure, it can be confusing. Reality is, these two ideas are related in some ways but not remotely the same in other ways. Plus, each is very good at accomplishing the job it was designed to do – as long as the user understands the problem to be solved and the specific purpose / output of each approach.

So, you want to understand these ideas better? OK, get ready for the Drillin’ …

Today’s question is from a fellow Driller who understands customer retention really well but just can’t decide on the best metrics to measure retention in the supplements business. Should he use Customer Retention Rate? Customer Churn Rate? Hurdle Rate? Ahh, to make the right choice here the gory details will need to be visited – so let’s get to the Drillin’ !

Q: Hi Jim,

I am here choosing all the metrics I will use in the coming days to evaluate the health of my business and learn a little bit more about it. I will begin analyzing some basic metrics and then (just after being completely comfortable with the “basic metrics”) I will do some more sophisticated analyses like LTV and RF Grids. (Jim’s Note: RF Grids are advanced customer LifeCycle tracking tools described in my book).

Now I am trying to decide which is the best metric to measure my site’s ability to retain customers. There are three metrics that come to my mind. Customer Retention Rate, Customer Churn Rate and Hurdle Rate.

Customer Retention Rate would be the easiest to measure but the least precise. I could be doing a great job retaining customers but if I am attracting a lot of new customers this metric could give the wrong impression that we are doing more poorly than the last time we measured.

Customer Churn Rate is very easy to calculate when you have a “subscription model business.” If the customer cancels the contract it means a defection. But in my case there is no contract. We sell products. If the customer does not purchase in 30 days it doesn’t mean necessarily that he defected.

The Hurdle Rate based on Recency (45 days for purchase seems to be a good number for the products we sell- natural supplements, based in Brazil) seems to be the best metric I can choose to measure our ability to retain customers over time.

What metric do you think I should be using to measure our ability to retain customers?

A: I think you are one of the smartest IT guys on the subject of database marketing, that does not do database marketing for a living, I have ever met (?) ! Where did you learn this stuff? Did you read a book or something? ;)

Your analysis is absolutely correct on every point, and the approach is on target. If you start simple and work towards more complexity, you will learn more about your customers. And assuming most of your products are roughly a 30 day supply, 45 days is an excellent cut-off for a Hurdle Rate analysis. Simply track the percentage of customers who have made a purchase in the past 45 days over time, perhaps monthly to start. If the percentage is rising, you are getting better at retaining customers. If it is falling, you should be looking for reasons why this is so.

Continue reading Choosing Customer Retention Metrics for the Supplements Business


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