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This is similar to the Adobe article on HN yesterday. Link bait for real improvement through statistical analysis, then the article undelivers.

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Once we figure out if this model actually reduces churn, then we'll be happy to share.

However, you should be aware that there's no silver bullet here. The algorithm we choose might work brilliantly for us and terribly for you.

I wrote the post to get people thinking about how to use data and behavior to drive down churn.

I'm well aware. It comes down to the right combination of an algorithm and heuristics. And it's the heuristics part that is rarely transferable from problem to problem, the part you laid out in bullet points for your hired gun.

I'm just interested in understanding the methodologies, and "cherry-picking" what's applicable to my problems.

What people seem to be commenting on is that there's a difference between reducing churn through econometrics, and an attempt to do so. The title asserts the former, that the post contains an answer.

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