Click-throughs are the currency of the recommendation nation. The more choices you make (or decline to make), the more finely tuned the recommendations become. The more your peers interact with Amazon, the better Amazon’s engines can infer which recommendations will make the most sense for you and the most dollars for them. The result is that recommendations can become breathtakingly profitable examples of what economists call “network effects,” where a network’s value is proportional to the number of its participants.
But as useful as these algorithms can be, they’re also subject to sudden bouts of apparent blindness. It ticks me off, for example, that Amazon’s recommendation engines do not intelligently distinguish the books I browse or buy for me from the ones I browse or buy as gifts. Yes, I can click a little box when I buy something as a gift. Additionally, if I visit “My Amazon,” there is a tab that offers to “improve my recommendations”: on the long scroll of everything I have bought, I can click a box that says “This was bought as a gift” and another box that says “Don’t use for recommendations.” But these features are far from obvious (I discovered them only in writing this review, and I use Amazon a lot). Nor do Amazon’s engines use my history of gift buying to suggest presents for particular friends. Would such suggestions bug me? No. In fact, I’d like Amazon to make it easy for me to switch back and forth between browsing for myself and browsing for others. I’d cheerfully choose to be a recommendation beta user if such an option were offered–much as I’d be happy to have a “personal shopper” help me out come birthdays and holidays. Just ask nice.
Different issues emerge with the “Just for You” recommendation engine at Apple’s iTunes, which was introduced in 2005. I can forgive the fact that my purchase of Bohemian Rhapsody prompted “Just for You” to recommend The Best of Foreigner Live, but not that buying Van Halen’s “Dance the Night Away” provoked a recommendation for Rush. While I accept that recommendation engines have their own quantitative quirks and eccentricities, those suggestions are just terrible. Apple’s engine appears to give more weight to era than it does to genre, tempo, or style. (An Apple spokesperson whom I contacted declined to be more specific about how its recommendation engines work.)
Apple’s recommendation software is worse than Amazon’s in other ways, too. When I buy a song or two from one band, why does the engine ask if I want to buy an entire album from another? I should get individual song recommendations before I get album suggestions. Apple’s iTunes pushes albums and songs: it feels like a hard sell. I want to be sonically seduced, not commercially assaulted. Get me to sample–for free, of course–another song before asking if I own or want to own the entire album. If I like the song, I’ll buy it. Honest!
The “Just for You” interface looks pretty enough. But as an interactive experience, it’s displeasing. Unlike Amazon, the site feels more like a record shop that wants to move product than the den of a friend with great taste in music. Recommendation engines should liberate retailers from bad online store design, but the iTunes site reminds me of what I like least about shopping. Where is Jonathan Ive, Apple’s legendary industrial designer, when we need him?
Hear more from Google at EmTech 2014.