Twitter is frequently lauded as a triumph of simplicity. “It should be Twitter simple” can be heard punctuating discussions around new product development.

To the contrary, I think Twitter is complicated as hell. Explaining the value proposition to an internet-savvy person accustomed to a service like Facebook can draw the same blank stares as explaining it to your grandparents. The 140-character limit feels arbitrary and limiting. Twitter search, a product with incredible value, remains hidden from the general public. Dozens of clients and hundreds of Twitter-based websites add to the cacophony.

Part of the reason it’s so difficult to explain is that it’s not a website and it doesn’t have an explicit purpose, meaning the conventional vocabulary to describe online properties fails here. It can be better seen as a medium of communication where the value proposition is completely contingent on how the person chooses to put this medium to use.

All this, just to say that I am loving the Cocoa IV drip from @scottstevenson and @cocoadevcentral even though it represents a departure from my approach of only following people that I’m somehow personally acquainted with. I also have a thing going on with the robot from @popurls, who’s got some jokes.

Recently, Cameron Marlow, helped publish some numbers regarding the nature of relationships on Facebook, finding that most people, while having upwards to a couple of hundred friends, only actively interact with about a dozen of them. This was consistent with other off-line studies that showed the people we actively correspond with and the people we are close with are quite finite in number — maybe even suggesting a limit in our capacity.

While the data crunching wasn’t meant to be empirical or conclusive, it did offer a look at a new class of relationships: the relationships we maintain passively, through products like the Facebook News Feed. The number of people in this relationship segment was significantly higher per individual. Whereas we communicated directly with about a dozen people, we passively maintained a relationship with about 30 people. Cameron describes this class of relationship management:

This consumption is still a form of relationship management as it feeds back into other forms of communication in the future. For instance, a high school friend uploads a photo of her new puppy and this photo appears in your News Feed. You click on the photo, browse through a host of other photos and discover that she has also gotten engaged, which may lead you to reach out to her.

I think there are meaningful parallels (baseless assumptions) one can draw between our capacity to maintain relationships and how we interact with websites.

Without my RSS reader, I oscillate between a handful of sites, outside of which, I struggle to find a new vector for my web surfing. There is the “core” group of sites that I visit very regularly with maybe a couple of dozen supporting sites where my visits are driven by a specific context (i.e. share a photo, read product reviews, post a link, etc.) or because I happen to remember about it. This list of core sites has not grown much in size, but members of that exclusive club are always changing.

A lot of consumer sites that are being created are done so under the pretense that they will be “destination sites” — a site a user will explicitly choose to visit for one reason or another. Assuming the number of our core sites remains relatively constant — achieving destination-site-mindshare is an uphill battle, since it means unseating an existent core site. Your value proposition needs to be that much greater. For that reason, most people visiting your site will be new and most of them will not come back.

I think this stresses the importance for your website to broadcast in some capacity and provide the means for people to maintain a passive relationship with your website, which in turn creates inroads for a more directed interaction down the line.

Addendum

For the fun of it, without the aid of my feeds, my current core sites for an information fix are:

• Digg
• Reddit
• Hacker News
• Huffington Post
• Daring Fireball
• Boing Boing / Boing Boing Gadgets
• NYTimes

What are your core sites?

Maybe even more interesting than trying to guess on the sites, if you use Safari 4, a screenshot of the Top Sites feature would probably be quite telling. (The Top Sites feature seems to support the idea that the list of sites we interact with most-often is rather finite.)

This comes from an internal Google memo, from Jonathan Rosenberg, SVP of Product Management, that was later released publicly.  Its tone is thoroughly optimistic but more importantly it lays out some of Google’s theses on the future of the web.   Particularly interesting is the piece on content creation, which stresses the importance of experts to craft our data, a very under-represented view point in new product development.

Systems that facilitate high-quality content creation and editing are crucial for the Internet’s continued growth, because without them we will all sink in a cesspool of drivel. We need to make it easier for the experts, journalists, and editors that we actually trust to publish their work under an authorship model that is authenticated and extensible, and then to monetize in a meaningful way.

He also communicates a bias for making all information available, dismissing the common model that charges for access to interesting data.

All of our products should reflect our bias toward giving our customers, users, and partners as much data as possible – and letting them do with it what they wish.

This makes sense if you’re Google, where the scale of information only compounds value to your core search product. I still think the ‘old’ model of packaging and selling access to such data has some legs left, especially if you’re a small  company focused on extracting intention-based data from a valuable niche.

You can segment the data into two types: noun-based data and intention-based data.  Noun-based data is mostly descriptive of the world around us – specs of a phone, who our friends on facebook are, etc.  This data, without a question, should be made freely available for all to use.  On the other side is intention-based data.  If you run a poll that asks a user to rank which aspects of a phone are most important to guiding their purchasing decision, you’re taping into intention-based data, the same type of data that google makes all of their money off of.

Intention-based data is a bit harder to set free, partly for reasons of privacy, but also because it’s intrinsically valuable.  You need to work hard to create value around noun-based data, that’s why it makes sense to set it free.  The richness of functionality that the Twitter and Facebook API’s created could not be possible if either company hoarded their data.  Intention-based data is different, it has implicit information leverage.  As soon as you set it free, you remove the leverage that creates the value to begin with.  You want to be the conduit of this data.

Over on the Adaptive Path blog, Brandon Schauer shows off a couple of nice diagrams, illustrating how new products typically get approached, how they they’re perceived, and how they should be approached.

How not to do it.

What the user sees.

That looks about right.

I’m a little bit divorced from the original context of the diagrams (“how businesses approach delivering value to their customers”?), but I was only thinking about something like this yesterday. What comes first, the interface or the data model?  There is no question, that the diagram of user’s perception of a product is spot-on, they could care less how and what you’re storing on the back-end.  However, with a complex-enough problem, it’s hard to make informed inroads without exploring the interface and data asynchronously.  

The user research and design process will always have the first stroke, but to understand the data and solve problems around the data is to acquire domain-specific knowledge of the problem space.  For instance: to meaningfully organize a product spec page for a laptop, you need to understand the data that surrounds a laptop.  And if you’re not using a more realized data model, you’re effectively using “lorem ipsum” and a lot can be said about the deficiencies of that strategy.