Chris has an interesting piece on recommendations:
“In a sense, you can think of all your filters as being part of orthogonal trust networks, often with the only common member being yourself. They rarely, if ever, overlap. Thus any service that tries to condense all of your different planes of influence into a single dimension is going to fail, at least as far as useful recommendations go. That isn’t to say that such services shouldn’t offer playlist sharing and Amazon wishlists, only that I’m likely to find better advice elsewhere.”
His point is that recommendations from within your existing networks aren’t necessarily the best, or, for the newest, bestest, coolest products. He recalls Bill Joy’s quote:
“”No matter who you are, most of the smartest people work for someone else.”
The same might be said of recommendations. No matter who you are, someone you don’t know has found the coolest stuff.””
I tend to agree that what lives in the recommendation engines is becoming less and less valuable as a recommendation. They seem, more than often, to be engineered from within a review or fan base. As communicators we are going to have to increasingly look outside the established networks for the orthogonal recommenders. I’ve been speaking of this for awhile now as the difference between right-field (known to you) recommenders vs. left-field (surprising) recommenders. Smart buyers will move to the left field while triangulating off the right, and, ignoring the pay-to-play engines.