Found a pretty interesting Web Analytics Blog that I did not know about before called Analytical Engine that seems to cover analytics as it pertains to customers; it's not all that often I see that so I subscribed to the feed for this blog.

In fact, there's a Predictive Analytics Report which I just downloaded that explains "churn rate" and gives a lot of real life examples.  Among the areas covered in the predictive analytics whitepaper are:

"…Cross-sell/upsell, campaign management, customer acquisition, budgeting and forecasting and attrition/churn are the top 5 application areas for predictive analytics

1. Median investment of companies with successful predictive analytics programs is $1M annually (60% of which is on resources, 20% on software, 15 % on hardware)
2. 56% of a predictive analytics project time is spent on definition, data exploration and preparation

This sorta reminds me of Eric Peterson's new process to diagram out all web analytics processes in order to find out if your measuring what you need to measure and how to best do that.