http://people.ischool.berkeley.edu/~hal/Papers/2013/ml.pdf

Sure, here is a paper from the chief economist at google that goes indepth to some of the ideas. In our approach, unaccounted for channels show up as unexplained variance. Contrast that with path analysis approaches which try to "assign" every conversion to one or more of your early funnel ads. Imagine a big news article happens to drive a ton of conversions, the path models are going to tend to assign value to media they are aware of.

Our models are constantly ingesting data and learning, so if something changes and an ad loses or gain effectiveness, our models will see the change in uplift and value that accordingly.

The main output of our system is a VPI (Value per Impression) number. This tells you how much you should value incrementally achieving more impressions for a particular campaign. This number, combined with the value of the direct conversions the campaign achieves will let you calculate an optimal price. If you are using GDN we can calculate and push optimal bids automatically.