From TheFutureOf (19 Sep 08): Responding to Jim Novo’s 29 Aug 08 10:54am comment

(sorry, no copy of Jim’s comment)

Howdy.

No, I didn’t know much of your effort is toward “teaching”. I’m happy to learn, though. This also helps me to understand your point of view. You favor “simplicity” and in teaching models I favor analogy and metaphor, often starting with very simple models and building upon them.

Done and done. Thanks.

Yes and Hear Hear! to your “forge direct links between the various behavioral sciences and successful marketing efforts.And it seems to me we’re doing that!” One of my goals for this blog is being realized. Thank you for helping me to realize a goal.

You write “I would not suggest anyone use the Recency metric without some kind of segmentation, because since we are talking about likelihoods here, you need a coherent population of some kind. The error rate when looking at a single individual would be high, but across a population, again speaking to “likelihood”, it’s a great yardstick for placing your bets.” Yes, yet another example of people making first order estimates based on inadequate data because they failed to figure out the basic parameters of their experimental systems.

Then you offer “…sometimes you find that the Recency relationship is not as simple as it is at a more macro level, not as linear as ‘the longer it has been, the less likely they are to repeat’.” and I’m chuckling a bit.

Your description of response and profitability curves, etc., leading to new segmentations makes me think if the way we (NSE) uses Bohmian and Mandelbrot methods could provide a worthwhile predictive solution to this.

(you were just itchin’ to get “dis-Engagement” in here, weren’cha?)

Good thoughts and reasoning. Variable clouds v segmenting? I’m not sure having two options makes things simple enough.

(laugh, darn it)