This post is one of those gems that simply needs reiteration:
Not that beer and the future are incompatible, heaven help us if they were, but it’s not just cell phones. Clothes, music, a whole generation of young people who, like people who think nothing of heading off to another country for a weekend techno festival and will in the future, no doubt, think nothing of heading to that same country to close a deal in fifteen years.
Screw “east meets west” let’s jam on “today is yesterday’s tomorrow”.
currently playing: Acumen Nation “Dreamheart/Crush’d”
A comment made by False45th’s Flatlander, in addition to some other recent ruminations had me thinking lately about the coming(?) era of programmatic serendipity in our socially aware apps. This is something I keep hearing about in the context of Web 2.0 esp. w/r/t/ apps like Flickr, del.icio.us, and even /shudder/ things like Friendster and MySpace.
What’s cool here is the way that the participating community marks things up, creating these powerful opportunities for other participants to explore and discover exciting new content and perhaps even make some connections while they’re at it. The possibilities are only a hair shy of limitless in all directions of intriguing, electrifying, and terrifying. Now, mesh this in with commerce (that ol’ familiar dialogue) and we enter into some new facets of this gem, many of which are unexplored.
Taking Amazon as an example, there’s certainly one place to start. Amazon has no tagging system per se but they’ve got some robust customer data with which to make some calculated inferences. If you’ve ever browsed through their recommendations though, it can be pretty hit-or-miss. (On my visit just now, I noted 5 of 30 that I’d be reluctant to examine and another 6 that I’d previously flagged as “I own this” or “not interested.) On the other hand, each item is peppered with user reviews (with varying degrees of coherence), links to (usually) relevant lists of like items, and “In Addition To…” and “Instead of…” recommendations. All of that is useful but unfortunately feels like it lacks the simple elegance of a tagging system a la Flickr.
How do you make it all fit together and work?
How do you draw on a large body of customer data for your calculations and still allow for the kind of elegant serendipity that you see in Flickr-like apps?
Let’s take iTunes as the prototype app:
The idea is half-baked, I’ll be the first to admit that. And it also involves the willingness to surrender some of this information that you might otherwise think of as “yours” or “private”. And it would also involve some serious computing power and narsty statwerks. But hell, it sounded good at the time.
currently playing: Underworld “Juanita/Kiteless/To Dream Of Love”