Monthly Archives: June 2007

More on Customer LifeCycle / LifeTime Value

Adelino has chimed in with some great thoughts on LifeTime Value and ways to execute against it.  I’m all for a practical approach, which he has outlined.

A couple of further ideas:

1.  As counter-intuitive as it might seem, I think we’re better off talking about LTV as a concept and not a “number” in most industries – especially when folks are just beginning to look at this area. 

The idea that customers have “future value” is not a hard one to get across, the idea you can triangulate a specific “number” representing this value is difficult.  Tactically (which is what most folks care about), I like to use the idea of “relative LTV” or Potential Value – you don’t need to know a specific number, you just need to know which customers have higher versus lower Potential Value and allocate attention and budget appropriately.  This approach allows people to execute against Adelino’s final four points without the mind-numbing LTV math.

Another way to say this: if you manage Potential Value at discrete points in time – say as monthly “snapshots” – the “movie” of LifeTime Value will take care of itself.  For the more aggressive math folks, this begins do look like a “value curve” for each customer or segment where you can look at the slope of the curve to predict Potential Value.  Go all the way to derivatives if you want to…

2.  There is still a need to bolt all this directly into Finance and the Periodic accounting system.  If Marketers or IT folks can do that, now you have something really cooking.  The best way I have found to sit down and start talking about this is to break out Customer Productivity by Financial period, as explained here.

This approach gets Finance to start wrapping their heads around “Potential Value” as opposed to Current Value.  You could use Adelino’s “Profitable, Marginal, Unprofitable” model in much the same way – just configure the customer chart so that it explains why the past Financial Quarter was Profitable, Marginal, or Unprofitable.  “We had a great quarter because the % of Profitable customers rose while the % of Unprofitable customers fell”. 

They need to see it right in front of their Financial eyes.  You get a couple of Quarters in a row where your analysis lines up with the Quarter, and then you start predicting the Financial outcome of Quarters based on the Customer Value Model.  Once you lock the customer analysis to the accounting analysis like this, you’re in, because the next question from Finance is:

Can you do anything to affect this model?

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***** Bring Out Your Dead

Yes, a rare 5 star article, my “must read”.  Why?  For one thing, it is based on analysis and real-life data modeling by Professor Peter Fader and friends at the Wharton School – it’s not a trade mag article by some Consultainer.  Fader has a major track record in customer analysis and modeling.  The article is Beware the Walking Dead.

What we’re talking about here is the effectiveness of cross-sell and retention efforts based on the Customer LifeCycle, and how if you execute too late in the Cycle, you could end up “waking the dead” and driving defection rather than encouraging retention.  The specific example given is cable television, though this article provides support for a lot of ground covered on this blog and others, including my piece on engagement, and Ron’s numerous pieces on customer experience.  I love it when academia synchs up with real world experience – academics are so much more rigorous, you know…

The article is a summary of the results from the academic paper, and includes a link to the actual paper for those of you who are into the math and modeling.  If you’re unfamiliar with academic papers, they typically provide the actual formulas for the proof of the assertion.  Reading the actual paper is not for the faint of heart, but I know some of you folks dig the high level modeling math.  Not into the math?  Read the article itself, an excellent summary.

Bottom line: another reason to downplay the LifeTime Value approach in favor of Customer LifeCycles.

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