Friday, May 09, 2008

Learning to love customers like you

Michael Schrage at MIT Technology Review writes a fun article, "Recommendation Nation: Learning to love customers like you".

Some excerpts:
Recommendations are everywhere on the Internet.

Pop-ups and context-sensitive advertisements have been supplemented by this low, seductive whisper of automated suggestion. The truth is that I now get more good recommendations about more things, more often, from Bayesian algorithms than from my best friends.

Perhaps this should make me wistful, but it doesn't. Better tech­nology doesn't mean worse friends.

Unlike human recommenders, Apple.com, ­Amazon.com, and Google.com never insult me by implying that I spend my time, money, or attention on the wrong things. They're simply making relevant--and occasionally novel--recommendations based on my past choices and the things I attend to in real time.

The focus of digital personalization has shifted from what I am interested in now to what I might be interested in next. All the choices I make in the moment are absorbed into a sphere of suggestion where, after they have been statistically weighted, they are reborn as offers and advice.
The article goes on to talk about several ways recommendations could be improved so they would be more helpful.

I am briefly quoted in the article talking about the early motivation behind building Amazon.com's recommendations.

1 comment:

Todd B. said...

Cool! I'm eager to see the time when people recognize that their friends really don't share their tastes as much as well as strangers.