Principle 2: We don't need more choice. We need more TV Guides.

< PREVIOUS | NEXT >

Walk into a room of 1,000 people in which you know no one but know that there are some key people out there, somewhere. Where do you start? How do you start? Do you talk to anyone? With a crowd that large you may become so overwhelmed trying to locate the right folks that you’d leave talking to no one. Conversely, walk into a room of two people—it's a lot less threatening, easier to choose, and far easier to engage. In fact, no matter what type of person you are (extroverted or introverted), you’d probably have no problem introducing yourself to those two people and engaging in a conversation.

We live in a world with plenty of options; lack of options is not the issue. The problem is we don’t know where to begin, what to look at, or who to talk to. We all need some guidance.

Now those two people in the room you just met may not be your ideal match. But if you talk to them for a while, they may know someone (or know someone who knows someone) who can better take you to the information you need.

We’ve all heard the line “Content is king.” Well, what we’re all watching is content. Creating more of it is not the issue. There’s plenty of great content out there. We just haven’t had a chance to discover it. And for that, we need some help.

Much of the discovery has been focused through developing recommendation tools like those supplied by Netflix or Amazon. It’s the holy grail of personalized technology. Who can find the perfect computer-based algorithm that can facilitate accurate recommendations for the multitude of different customers and their varied tastes?

That solution can work, but people often become attached to personalities, real people who offer recommendations. This relationship works in reverse where the masses get to know an individual. You can never create an algorithm strong enough to match the influential power of an Oprah book recommendation. Oprah doesn’t know about all her viewers’ intrinsic likes and dislikes, but her viewers know Oprah and they want to hear her opinions.

We’re also directed to the wisdom of crowds where a mass of like-minded readers act as peer editors offering recommendations to each other. News recommendation service Digg operates in this way.

Another editorial technique is content analysis where tools or editors improve the classification of information. A perfect example is Pandora, a music recommendation service. Pandora employs musical analysts to look into the architecture of a song and classifies it on many attributes.

New media enables these three basic approaches—trusted advisor, wisdom of crowds, and content analysis—to flourish. It doesn’t advocate one approach over the other, but it does allow them to work in conjunction. For example, Netflix combines all three: content analysis (analyzing metafile of a movie), wisdom of crowds (personal ratings vs. community ratings), and trusted advisor (top recommendations from film critics, plus links to friends’ recommendations).

Trusted advisors require their audience to view them as such. This is the core of what makes a successful blogger. Over time, blog readers must develop a personal opinion of that blogger’s knowledge of the channel through reading and responding. At the same time, algorithms can get to know us, introduce us to trusted advisors, or to like-minded people. Ultimately, we’re looking to rely on someone or something to help direct us.

< PREVIOUS | NEXT >