Tag Archives: Customer State

New RFM: Segment Wireless Customers by Behavior or Demos?

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

If you’ve never actually segmented customers by behavior, it can be a bit tricky exercise.

Just remember this: if improved customer retention is the goal, you want to segment with ideas and data that will lead to metrics specialized in driving successful retention programs. For example, demographics are descriptive of the customer; segmenting by demographics will group customers by description. This segmentation does not really indicate anything about their behavior, so will rarely give you the tools or leverage needed to change behavior. If you want to change behavior, segment using behavior.

Make sense? Then on to the Drillin’ …


Q: I have taken up a new assignment in this new financial year in my company, a Cellular / Mobile connections provider. I would like some direction from you; also I have suggested your book to my management.

A: Well, thanks for the plug on the book and I’ll give the “direction” a try!

Q: Objective: To create loyal customers who become brand evangelists

Areas covered:

  1. To drive customer loyalty to ensure 80% of the customers recommend brand to others.
  2. Customer Behaviour Profiling: Create an action oriented customer profile, use profiles to create marketing & service programs to retain & increase value of customers.
  3. Predictive Marketing / Promotions: To predict the likelihood of future events based on customer models & to predict the profitability of a promotion to encourage customers to do what we want them to do & achieve the highest ROI (Return on investment). Predict when a customer is about to defect / leave us.
  4. LifeTime Value: To find what a customer is worth in the future and based on this to find how much you could spend on retaining them & still make a profit.

Please reply on how to start this activity?

A: Yikes! That’s a pretty long list of “areas to be covered”, you are going to be very busy! Some of it sounds pretty familiar too, like I’ve read it on my web site you might want to get that book after all!

The creation of retention programs always starts with customer segmentation, you have to understand the behavior you have before you can create programs to modify behavior.

That probably means starting with #4, LTV. You want to look at LTV by segment.

Get records of defected customers, put them in a spreadsheet or database, and determine:

  • Average length of time as subscriber
  • Average spending over that time
  • % of this spend that is considered “profit”, which you can use as a proxy for LTV.

In the beginning, you can use a company “profit” average for LTV until you get more sophisticated. In communications, the number often used is EBITDA Margin; ask your finance people what you should use to determine % of spending that is LTV.

Once finding the average, it is time to segment by different dimensions and determine the same 3 variables above for all the different customer segments. For example:

Spending quintiles – highest 20%, high 20%, middle 20%, low 20%, lowest 20% of
defected customers; what is average length of subscription, spend, LTV?

Product / service bundling – identify different levels of service / tiers / add on services of defected customers; what is average length of subscription, spend, LTV?

Source of customer – which ads / offers / selling methods originally attracted the defected customer; what is average length of subscription, spend, LTV?

Geography – using transmitter locations or other natural boundaries dividing the defected customers; what is average length of subscription, spend, LTV?

Hardware – group defectors by type of phone or terminal or other hardware; what is average length of subscription, spend, LTV?

Contract details – if contracts vary widely as to their basic nature and terms, group defectors by contract type; what is average length of subscription, spend, LTV?

After running these studies you should have enough data to logically and critically construct your other 3 initiatives in profitable ways.

Jim

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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

RFM and Customer LifeCycles

Jim answers questions from fellow Drillers

Topic Overview

Hi again folks, Jim Novo here.

Today we have a bit of confusion between RFM modeling and tracking Customer Lifecycles. Each has benefits and downsides, but the most important idea is to make sure you know what each is best at. Make sense? Let’s do 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.

Continue reading RFM and Customer LifeCycles