Brainnovate

For the longest time, I have been a fan of Digg, but never a big time user. I first signed up almost two years ago, and since that time, I have Dugg a few things here and there. But I never really got into it until the last couple weeks.

I am not sure what happened to be honest. My increased interest coincided with the launch of their new “recommendation engine” technology.  Maybe the release of this tool lit some inner spark, because I watched the videos, and immediately went on the site to play. Before I knew it, I was logging hundreds of Diggs, and reading article after article on how best to use (and benefit) from Digg.

Actually, I have always been a fan of “optimization” algorithms.  Over at Vertster we use something called the Taguchi Method to accomplish some pretty cool multivariate testing, so now you know why.

Anyways, the Digg recommendation engine is particularly interesting because on the surface it seems to give you more of a chance at getting noticed if you suffer from low Digg authority (ie you haven’t been doing it for long.)  However, in reality, it adds another layer of “black box” to the site- what we call it at Vertster when you have an unknown algorithm and all you can see are the inputs and outputs but have no idea what goes on in the middle.

On the surface it appears to give Digg another chance at separating the wheat from the chaff so to speak.  By analyzing a number of signals, the algorithm could display certain submissions more frequently than others.  It also adds a fertile new area that should earn more pageviews than the old standard upcoming page, which was nearly impossible to get noticed on without help from friends.

So what are these signals likely to be?  Well I am sure there are some very smart Diggers who are probably trying to decode this right now… but it will be tough because its likely to be a moving target.   Some of the factors I would expect to be included and weighted heavily would be the Digg authority of the submitter, and also that of the browser.

Of course the contextual matching engine is also at work- the part of the software that tries to show you stuff you are likely to be interested in.  But also, I bet there are other things like time of day, day of week, and current events.  These “moving targets” will make it difficult to decode the exact algorithm and should improve its effectiveness at showing sticky content.

I was reading the “Public Timeline” at Twitter yesterday and found a rather interesting web application. Many of you may be wondering how I have the time to read the public timeline… and well, I don’t. It was a moment of shameless self indulgence and Twitter exploration. I find it interesting to click people links to try and gain an understanding of who is actually using Twitter beyond my own network. As I have mentioned in my past posts, Twitter is currently made up of 1 million of the earliest adopters, so you are bound to find something interesting. Does TwitterStumble exist yet?

What I found is IdeaCV- sort of a social brainstorming and innovation tool. This is almost identical to my original vision for Brainnovate, before I decided to just build a blog with it. In fact it was the reason I registered this domain name in the first place.  Ultimately I identified a number of reasons why I didn’t want to invest the resources to do this, so it became a great name for a blog about innovation and brainstorming instead.

Here is how it works and why its an interesting idea: Brainstorming and coming up with great ideas is tough, and its seldom a solo endeavor. With IdeaCV, you post your idea to the site and get immediate feedback from other users, hopefully helping to refine the concept. Other users post their ideas, and you can help them by offering suggestions, criticisms, etc.

The site is well executed and appears to be built using one of my favorite innovation tools- Ruby on Rails.

The company behind this site, Increo Solutions claims on their site they are just getting started and expect to have more on the way, but their site just says that the software is in alpha. We’re looking forward to seeing what they come up with. I am guessing some kind of enterprise version where you can lock down outside access to the system.

Personally my biggest complaint about sites like this revolves around intellectual property, and that people are generally unwilling to share their ideas publicly. If I have a great idea, the last thing I am going to do is go and post it in a public forum for other entreprenuers to “cherry pick” and then become my competition.

Then there is the whole concept of who owns what. If you post the next Facebook, and the core concepts are developed collaboratively, isn’t that like wearing a target on your back that says “Sue me?”

The best part for me anyhow, is that I no longer feel compelled to build something like this.

Michael Arrington pointed out a new service this morning that I was not aware of for keeping tabs on what links get tweeted the most at any given time.

Twitturly is kind of like a Digg for Twitter. It takes a pulse of what the 1,000,000 or so Twitter users think is currently important by displaying a “Digg like” list of the most popular links. As links get passed around, they show up on the Twitturly radar, and get “voted” up the page. Arrington surmises this may help increase the editorial value of Twitter. In my opinion, services like this (there are others)-

1. Can help people quickly see what arguably the 1,000,000 “earliest adopters” think of various interesting new things out on the web. This is how Digg is supposed to work as well, but it has gained much broader acceptance and has become the target of spammers, etc.
2. Is yet another service that points towards Twitter winning the micro blogging platform wars- despite questionable service quality. As I mentioned in “Are Twitters Marketing Problems a Marketing Ploy?” - the best option out there is not always the winner.

A big problem I see right now is a general lack of numbers. Being a numbers/math guy I cannot look at something like this without considering the stats behind it. With a total sample of 1 million Twitter users, are there enough to really trust these results as “statistically reliable” of what the greater audience thinks? I tend to think not. But it is still an interesting way to see some new sites.

For some reason I had never heard this term before. The “Fortune 5 Million” represents focusing a product or offer on the millions of overlooked small businesses 1-50 employees. These little companies can’t afford big “enterprisey” type solutions and have similar although slightly different needs.

I think this term was first coined in 2005 by 37 Signals, although I can’t say for sure. Last night I started watching the excellent Startup School videos out on the web, first with “David Heinemeier Hansson at Startup School 08″

As you may know, David is the guy who created the wildly popular Ruby on Rails framework, which I talk about in this blog.  However, this video is NOT about Rails, but focuses instead on building a profitable, sustainable business.  In his typically charged and humorous style, David makes some great points about why trying to be the next Facebook is akin to being killed in an act of terrorism.  At only 30 minutes, you are really doing yourself a disfavor NOT to watch this video.

One of the points David tries to get across is the importance of the Fortune 5,000,000 and how his company, 37 Signals, has built their business appealing to this market.  So today is Friday, carve out 30 minutes and go watch “David Heinemeier Hansson at Startup School 08.”

Twitter was having issues again this weekend.  If you use it, you probably know that by now.  The service has been plagued by various availability issues since it’s inception.  The funny thing thing is that every time it goes down or has any hiccup, the blogosphere goes nuts.  Dozens (maybe hundreds) of bloggers swoop in and write posts about the service, its’ problems, and how great it is when it works right.

If you believe that no press is bad press, this could be a very good thing for Twitter.  Surely a faulty service can’t survive forever, but anyone who has studied business (or been in business) knows that the best quality product isn’t always the one that wins.

So I pose the question… are all the problems actually helping Twitter gain mass acceptance?  Every problem they experience brings tens of thousands of dollars worth of free press, and spreads their name further.  Its an interesting feedback effect, and surely one that can’t go on forever, but interesting to watch nonetheless.