We love games here at Zeek Interactive. We play them. We make them.
And we’ve felt for a long, long time that games and learning were meant for each other. Our first training games were launched back in 1998 as part of a collaboration with AdOut. They were called “Monster Commands” and “Key Commando” and they taught the important key commands that made the AdOut production artists some of the most productive in the industry. They were a huge success. The employees loved them and within an hour, they had mastered key commands for programs like Photoshop, Quark and Illustrator that would otherwise have taken weeks or months to learn.
In 2003, we attempted to turn our game creation experience into a training solution for corporations. We created Motus Learning Systems with a couple of other partners to give it a focus. Motus built several demo games for different companies, and we even created a kids game to teach mousing skills. The initial illustrations for that kids game are shown above. And although this proved to be a short-lived venture for many reasons, it didn’t alter our belief that games are simply the best way to learn things that require repetition to master.
This past week, Gist launched their own training game. And I really like it.
Stated very clearly on the front page of their site, “Gist helps you build stronger relationships by connecting the inbox to the web to provide business-critical information about the people and companies that matter most.” Others, like Dustin Luther, have written about how Gist is helping them manage the many online relationships they’ve fostered. I like it too, but I really like their newest feature, a game called, “Learn That Name.” And it does exactly what the name implies… it helps you learn the names and companies of the people you follow on social networks.
It’s a simple game, as most good training games are. You’re presented with a person’s avatar and you get points for guessing their name correctly. The faster you guess, the more points you get. Get it wrong and you lose 50 points. Each round is five people. For my taste, it’s just the right number. In my first round I achieved the “Super Socialite” level, though I was lucky to get five people I know pretty well. The second round labeled me a “Casual Networker.” I think the game could do a better job of sensing the sex of a contact. If I didn’t know that was Geoff Livingston, it would be a lot harder to figure out if all four names were male oriented.
The game strips off choices as the time clicks by and the points drop. So, if you don’t know who someone is, it helps you. If you don’t get the name right, you don’t get the option of the bonus question, which is “Where does <first name> work?” I wasn’t sure who this next guy was, so the game gave me some help.
I haven’t used Gist much since I loaded it, but I’ll be using it more now. I think they did a great job with the game. I can see lots of potential for categorizing contacts based on upcoming events, recent additions, high school classmates, etc. In fact, I’d download this app JUST to play this game. After just a few rounds, I’ve already become more familiar with some folks I’ve been trying to get to know over the past year. And I was surprised by some of the faces I recognized and how hard it was to place their name.
Kudos to Gist. Well done.
If I’m a business, I’m hoping guys like me and gals like my wife change their mind fast. Why? Because these services represent a major opportunity to influence our buying decisions. And the 
I’m live blogging 
I’ve spent at least a year in a complete blogging funk. And it’s not because I don’t have things I’d like to say. I most certainly do. The reason for the funk is that I’ve been having an internal battle between “what I should be doing” and “what I really love to do.” Luckily for me, what I really love to do is also what I’m really good at. And it’s not creating and defining marketing strategies.
So, although we were running a 100% Macintosh office and had no worries at all about our systems being impacted by Y2K, the newspapers were very concerned about the power company and required that we rent a LARGE generator to kick in when the lights went out at 12:01 am on January 1, 2000. Of course, that never happened. And, truth be told, none of us at AdOut ever thought it would.
Some very well meaning, very smart people are being distracted by the lure of shiny objects. And they are distracting others in the process.
Signal VS Noise: A Look At The REBCNASH Twitter Stream
I wasn’t going to write this post. I obviously changed my mind.
This is a post about REBarcamp Nashville, but it’s not really about REBarcamp Nashville. Nothing I’m about to say has anything to do with the quality of the 51 sessions that took place during the day at REBCNASH. From everything that I’ve heard from people who were actually in attendance, Brian Copeland ran an excellent REBarcamp, filled with great information and attended by many who were new to the Web 2.0 space. One of the speakers I spoke with mentioned that he was pleasantly surprised by how attentive the audience was. He said that many were taking notes on actual paper, with actual pens.
Signal vs. Noise
I decided to monitor the Twitter Stream for REBCNASH based on a conversation I had the previous day about the volume of noise that was coming from conferences and how hard it was to find valuable content in what was being shared via Twitter. The claim was that these conferences were becoming polluted with noise. They were echoing the feelings Matt Stigliano had while trying to listen to the content being generated on Twitter at SXSW. And I remembered clearly watching his cry for people at SXSW to do more than just broadcast their Foursquare data. You can read about it here: Two Weeks of Social Media Hell.
This is no scientific study, but I did want to be as accurate as possible. So, I cross referenced my main monitoring, using Tweetgrid.com/irc, with Twazzup and Twitter Search,. Luckily, the Twitter gods were kind and the search stream was consistent between the three tools. In total, there were 184 tweets that used the hashtag #rebcnash that day. Those tweets were generated by 77 different people. I don’t know how many were in attendance. It doesn’t matter. What matters is that 77 people decided that they wanted to use the hashtag on Twitter to share something about the event with the rest of the world.
To analyze the content, I brought the tweet stream for REBCNASH into a spreadsheet and categorized each broadly. A tweet was either “signal” or “noise.” Since REBarcamps are learning conferences, I defined signal as any tweet that gave a piece of information that contributed to learning, or a provided a link to something that might. Everything else was considered noise.
Out of the 184 tweets, I only considered 8 to be signal. And when you see the 8, I think you’ll agree that I’m being generous. Here are the 8 “signal” tweets:
Again, I think I am being VERY generous here. Example, I included Jeremy Helton’s tweet because it might cause me to go take a look at Social Fusion. So, I counted it as signal. I could debate the “signal worthiness” of several of the others, but this should give you a sense of how low I set the signal bar. Retweets of these signal tweets (only a few) were not counted as signal.
A Closer Look At The Noise
So, the math is pretty simple. If only 8 tweets were signal, 176 were noise. Example: “no sweet tea here at #rebcnash yet but always hope. Had some awesome sweet tea the other day though. Must have more
” Which is a perfectly fine tweet, (I’ve said similar things on twitter while at a barcamp) just not signal by my definition. There were, in fact, almost as many tweets about tea, 6, as there were tweets that contained any real content.
Praise: these were tweets that simply praised some aspect of the conference without really providing any insight. An example of a praise tweet: “Can’t wait to line up the rest of the afternoon at #rebcnash.” These tweets contained the most used word at REBCNASH, which was “great.”
Questions: these were tweets that were predominantly coming in from outside of the barcamp itself. There were 17 questions asked. Only two of them were answered using the hashtag, one of them by me. An example of a question tweet: “Which is the best Twitter app for a Palm Pre? #rebcnash.” This was never answered.
Statements: these were tweets that simply made a statement, often seemingly random. An example of a statement tweet: “Learning more about twitter at #rebcnash” and “Is hanging and sponsoring #rebcnash today. Loving ‘Love is the Killer Ap dude’s jacket!” The last one could easily have been put into praise or even location as well.
Location: these were tweets that simply let people know where someone was while they were at REBCNASH. An example of a location tweet: “Second half of #rebcnash has started! (@ REBarCamp Nashville w/ 10 others) http://4sq.com/ai3HWT” The majority of these were not Foursquare posts, however, just people letting us know what session they were in.
Photos: these were tweets that contained photos. An example of a photo tweet: “#REBCNASH Schedule is Revealed! http://post.ly/dmq4″ Many of these also contained praise or a location or both, but were only counted in the photo category.
How Do We Increase The Signal To Noise Ratio?
I’m not here to debate why so little content was placed into the Twitter stream during this REBarcamp. There was no WiFi at the event, so a livestream was not possible and computer access was limited. I get it. And once again, just to be clear, those who actually attended are saying emphatically that the information shared in the sessions was excellent. Clearly, however, desire plays a role. First and foremost, you have to want to create valuable content or want to consume valuable content to make any of this work. And you certainly have to be able to identify what valuable content looks like in either case.
Personally, I’d like to do a better job of sharing valuable information. So, for those who have the desire and the ability to recognize or create good content, how do we make it easier to get more signal into the stream and get more signal out of it as well. @jazzychad has done a good job with Tweetgrid.com/irc and an even better job with Madch.at, but even those miss the mark on many levels. In this specific case, if you were interested in gleaning some knowledge from the REBCNASH stream, having the very best listening tool in the world would still have only netted you, at best, 8 potential nuggets.
And having the best tool for sharing great content only works if people actually share. From my own experience, I know I am more diligent to present quality information if I know it has some legs. It’s one of the reasons why we’re creating the Live Blog app. When I know the information I’m tweeting at an event is going to live as content on my blog, I’m more careful to make sure it’s good content.
Some Questions
I’m not sure I have the right answers for most of those questions, but one thing I do know for sure is this - I’m personally going to give more thought to the content I’m sharing at the next event I attend. I’m going to shoot for more signal and less noise. I think everyone will benefit. Including me.
Tags: noise, rebcnash, signal, Social Media, tools, Twitter
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