This hasn't been passing us by! Netflix were the ones who decided to make RMSE the criterion for their contest, and put up a million dollars to ride on it for good measure, so it's hardly a surprise all the papers are focused on it. Of course, RMSE doesn't measure user satisfaction; that's why we write papers describing the techniques that seem to work, and it's up to Netflix (and other recommendation service providers) to pick which of those they want to use given that they're maximizing something slightly different.
It's true that not being in academia that I don't hear the conversations that fill the gaps between publications. But if one's simply going from the published output on collaborative filtering at the moment there has been some convergence on RMSE as a benchmark. That's understandable, since it's easily measurable, and as you say, there are some folks throwing $1mm at it (which really isn't much considering what it'd do for their sales).
