Not going to agree with you there. Aggregation does nothing to make polling results more accurate, all it does is allow the "aggregator" to stake out a middle-of-the-road claim that will of course place them closer to the end result than roughly half of the individual pollsters, whom the aggregator will use highlight his "success" (along with a wide enough MOE to account for reality to be different than anyone's guesses).
It is quite true that it's GIGO (garbage in, garbage out) as well -- and the input polls are garbage, even more so than usual.
Aggregation (meta-analysis) substantially improves the "accuracy" (for example, margin-of-error & confidence level) of the analysis of the *combined* data-sets.
At the end of the day, Silver and Wong’s predictions were *extremely* accurate:
http://election.princeton.edu/2012/11/07/after-the-storm/
We may not have liked the results of their techniques this time around.
But after producing these sorts of results three elections in a row with impressive and increasing accuracy and precision, we ignore them at out peril in terms (for example) of judging the ongoing effectiveness of campaign strategies.