I didn't see every talk (my brother lives in the area, so I took a break to see family) but I did have a fun day at RATS. There was a brief introduction by Chris Anderson of Wired/The Long Tail fame (on video -- I was disappointed he couldn't make it in person, I wanted to meet him), which was very interesting. I was pleased that as he was talking he kept mentioning power law and lognormal distributions; I knew he mentioned my survey on his blog at one point, but I (and others, as expressed to me later) were still surprised he mentioned them together when discussing long tail issues. That nicely set up my nice "survey talk" on lognormal/power law distributions. This was followed by the excellent talk by Aaron Clauset on power-law distributions in empirical data, discussing the challenging issues of how do you determine, based on your data measurements, whether you're looking at something that seems to be following a power law or some other distribution. (I'm asked this question a lot; happily, I can just point people to Aaron's paper.) Sharad Goel gave a fascinating talk on the implications of the long tail in marketing/web sales, arguing that the "value" for sites like Amazon in offering the "long tail" of items is NOT necessarily in the additional sales, but in the power of locking in customers. (Since Amazon has "essentially everything", at a reasonable if not optimal price, why bother wasting time going anywhere else?) Neel Sundaresan of eBay discussed insights form eBay data about the differing "shape" of different market segments, and the implications for assisting customers to find items in the large landscape that is eBay. Silvio Lattanzi talked about implications of power laws in compressing social networks, and on models for affiliation networks.
The slides, apparently, should all be up at some point on the RATS webpage, or I'll update with an appropriate link.