I quite liked the more technical parts of the article and practical modelling tips for customer churn rates. But... I would more interested in a focused, more terse, article just examining how the modelling techniques you use can impact your understanding of a given data set. The bullshitting for the premise just sort of kept me distracted... Unless a16z updated their page recently enough to be different, they very plainly say there are multiple types of churn, then provide two clear examples, here's the first sentence about churn:
> There’s all kinds of churn — dollar churn, customer churn, net dollar churn — and there are varying definitions for how churn is measured.
I also find it a bit of a disservice they don't discuss other churn types while dismissing the notion completely in the introduction. Statistics is a really "it depends" kind of subject and if you don't put forth good effort to explain the assumptions it can be really hard to follow and even harder to correctly apply.
Next, I find it a bit off-putting they mostly modeled their way out of the problem instead of addressing the bigger meta question "how do I find out if customer churn is a meaningful metric for MY business?" This is a big assumption made by the article (customer churn modeled correctly is useful) but not supported by it.
Finally, I find this in the conclusion to be quite simply HI-LARIOUS for how brazen it is; while, IMHO, kind of missing their own point:
> The numbers we've just computed are perhaps the most central of all for a subscription business, yet it seems like most people have never been thought how to properly compute them.
> There’s all kinds of churn — dollar churn, customer churn, net dollar churn — and there are varying definitions for how churn is measured.
I also find it a bit of a disservice they don't discuss other churn types while dismissing the notion completely in the introduction. Statistics is a really "it depends" kind of subject and if you don't put forth good effort to explain the assumptions it can be really hard to follow and even harder to correctly apply.
Next, I find it a bit off-putting they mostly modeled their way out of the problem instead of addressing the bigger meta question "how do I find out if customer churn is a meaningful metric for MY business?" This is a big assumption made by the article (customer churn modeled correctly is useful) but not supported by it.
Finally, I find this in the conclusion to be quite simply HI-LARIOUS for how brazen it is; while, IMHO, kind of missing their own point:
> The numbers we've just computed are perhaps the most central of all for a subscription business, yet it seems like most people have never been thought how to properly compute them.