Bar Camp Block was tons of fun, and huge success if you’re to garner such success from the quality of ideas shared and the amount of drunken revelry involved. Both score pretty high. It was great seeing people come in from out of town, from places like Arizona and Miami. There’s been plenty of coverage of bar camp block from great folks like Jeremiah Owyang, Jordan Sissel, and Kent Bye. I’m not going to reinvent the wheel here, but rather give you a Biz dev guy’s impression of what the two most interesting conversations were at Bar camp.
One of the most interesting discussions was on the social graph, moderated by Brad Fitzgerald of Plaxo, David Recordon of Verisign, and Joe Smarr of Plaxo. Brad’s article about the social graph. That’s what started this whole discussion.
Here’s the ADD summary: Many of you may have joined a social network like Facebook or Involver. You may also be messaging on tools like Twitter or Jaiku. The problem is each time you join a network, you have to add your friends, associates, and family all over again. And again. And again. And again. Lame.
That’s David over to the left and Brad to the right. You can just make out Joe in the corner too.
Aggregating the social graph allows users to port over contacts and relationships regardless of social network. The holy grail here would be that I can join Linked in, then join Facebook and transfer my contacts effortlessly, while allowing linked in users to send me messages and make changes which I receive in facebook. The problem is biz dev types will be slow to support this idea, simply because everyone interested in profiting from attention loves vendor-lock in. In fact I’ve been told point blank by one person that nobody will ever cannabalize their own market share by introducing free export of data.
This is incorrect for two reasons. First, fencing off you audience almost never works. Even sans-export feature, a more ambitious competitor is likely to provide a means of reconstructing relationships from email or other user supplied data. Just ask any old school AOL exec who was in denial about the emergence of the internet in the mid 1990s. Or ask the people in charge of biz dev for Sony BetaMax. You’re also just a feature away from users feeling it worth while to manually reconstruct their relationships because of a cool new competitor feature. That leads me to the second point: open data ironically maintains market share. Personally, I spend a disproportionate amount of time on one particular social network and check the others from time to time. A social network which allows a tight integration with my favorite portal stays relevant and useful in my mind. I’m far quicker to discard a social net cul-de-sac from my daily routine.
Here’s one example of what this may look like: most of my social activity is on Facebook, but most of my work related activity is on Linked in. There’s no real reason to discard either; this isn’t a crowded space. I like Linked in for business networking purposes as much as I like poking the heck out of people on Facebook. Both become even more indispensible to me if they share data. Which is not to say this leaves us with the weakest of differators in the form of brand equity. Rather, the whole point here is that tall this social graph discussion is simply an acceptance of the fact that one-size-fits-all doesn’t work for social networks any more than it does for Levi’s jeans. The best part is that the technology infrastructure to support this social netowrk mobility is already in place. As is a logo for this, which Brad probably drew in MS Paint:
If you’re a director level or above invididual tasked with any kind web presence strategy, you’ll have to deal with the implications of social networks, and network portability. It’s time to start thinking about this now.
The Crash of Web 2.0, Uh Oh!
Are we seeing a bubble again? What are the leading indicators of an inflection point of growth or market maturity? These were the topics of discussion at hand which Mukund Mohan was good enough to moderate. Basically this was a cool chat simply because anybody who’s interested enough to show up to Bar Camp is going to be interested in this.
The consensus (one I don’t necessarily agree with) is that Web 2.0 applications have hit the point in the product lifecycle where you cross over from research and development to growth.
Some of the leading indicators mentioned were matriculation rates at universities (and conversely, drop out rates), investment capital flowing in (or lack thereof), “mainstream” media attention (a sure sign of maturity), and investment in fiber. The idea here is basically we’ve been through the growth, maturity and decline of Web 1.0, and the patterns which developed back then should repeat themselves unless we proactively take steps to ensure a softer landing this time. And we should. I’m going to leave the details of the leading indicators for another time, simply because I’m going to write a blog entry solely about this topic.
The participants also spent time analyzing the differences between the previous rise of the web, and this turn around. For instance, the first wave required massive amounts of investment in infrastructure than does this wave. Web 1.0 hence was definied by the need for VC capital, barriers to entry for smaller competitors leading to a small number of competitors, and the 80-20 rule defining ratio of infrastructure cost to people cost. This time around, the infrastructure is easier and less expensive to acquire, and so the 80-20 rule this time relates the reverse – namely people costs to infrastructure cost. The result in turn should be a greater number of market players and a much longer shake-out and consolidation period.
Viva La Bar Camp
So my first Bar Camp was tons of fun. If you’re nearby a local Bar Camp and have the opportunity to attend, I highly recommend it. I’m going to try to time my next trip to China such that I can hit the Bar Camp in Shanghai as well – should be a great opportunity to find out how the discussions differ on the other side of the world. I’ll post if I can make it.