After taking the Stanford online machine learning course last Fall, I was very interested to hear the details about the model they used. Magic statistics appar

After taking the Stanford online machine learning course last Fall, I was very interested to hear the details about the model they used. Magic statistics apparently. While it is good to identify users that might be leaving, it does not do any good if the intervention strategy doesn't impact overall churn. There is also the other side of the coin. Let's say your model predicts a user as "extremely unlikely" to quit the site. If that user attempts to leave the site you may be more inclined to offer them incentives to stay, knowing they will accept a one-month 50% discount or something like that. Or perhaps their usage indicates the level of value they derive from the site, and so you can offer targeted pricing based on what you believe that class of user is willing to accept. If they user doesn't use the site as much, then maybe you could offer them an unlisted pricing tier that fits their usage profile. And this is why I am not a business executive, it just feels like throwing spaghetti at a wall.