The technology and technique of ‘collaborative filtering’ has been around the Internet for almost a decade now, and it’s slowly creeping into everything we do on-line. Collaborative filtering is basically a way of comparing your preferences about something (books, movies, music, whatever) against a huge database of other preferences. When the pattern of things you have liked is similar to another group of users, the system can quickly suggest things that they liked that you hadn’t yet experienced.
One techno-summary on the web describes the technology this way:
If you need to choose between a variety of options with which you do not have any experience, you will often rely on the opinions of others who do have such experience. However, when there are thousands or millions of options, like in the Web, it becomes practically impossible for an individual to locate reliable experts that can give advice about each of the options. By shifting from an individual to a collective method of recommendation, the problem becomes more manageable.
Most of us have experienced collaborative filtering on consumer web sites such as Amazon.com. Apple’s iTunes program is increasingly using the technology to encourage more purchases. (I just bought Chopin’s Fantasie Impromptu in C-sharp Minor, Op. 66 from iTunes, and my e-mail receipt suggested that I might also like Louis Prima and Aretha Franklin, which I do.)
The idea of collaborative filtering is directly relevant to arts managers for at least two reasons. First, almost every cultural transaction is what economists call an ‘experience good’ — the buyer doesn’t know what they are buying until after they’ve experienced it…long after their purchase decision. That fits the challenge that collaborative filtering seeks to address in very large groups. And it underscores the idea that our direct marketing efforts to consumers are relatively useless in actually influencing their decisions. It’s all about word of mouth, referral, and invitations from someone other than us.
The second thing arts managers can learn from collaborative filtering is that consumers are much more eclectic than we give them credit for. The artificial intelligence of iTunes made the connection between Chopin and Louis Prima. My local performing arts series would never have connected those two things (instead, they give me the chamber music series, the jazz series, the pop series).
There are great stories from commercial catalog companies that start to use collaborative filtering in their computers, and come up with combinations that nobody expected: ‘so you’d like to order pillows, a comfortor, and some sheets…can I interest you in some car tires today?’
Arts organizations need that same sort of informed surprise when dealing with their audiences.
