One of my personal / professional projects over the past year has included analysis of dozens of large in-person events. They have ranged in size and scope, but a short list of the events being monitored includes:

• Social Media Club Seattle (150 to 300 person events, held monthly)
• Display Week Seattle (5,000+ attendees)
• DEMO (500 to 1000 attendees, held twice each year)
• Seattle Chamber Tradeshow (5000+ attendees)

Having monitored these events online and in-person, there was a basic and simple theory I was working with: that attendee attention span and information spikes were ultimately at odds with each other. Continue Reading »

A lot has changed in the past few years. If you need a crash course in educational videos and statistics about the evolution of communication using social media: the following five videos are guaranteed to have at least a few facts and concepts that make you think.

I recommend sitting down and watching all of these from top to bottom, as three of the videos are part of a series (Do You Know 2.0, 3.0, 4.0) that came from 2007. While the information is old, the reality of trends in 2007 is now a historical footnote for 2010. As we see adoption take root with several technologies moving through 2012/13, some of these videos will find themselves into world economics and business fundamentals training. Continue Reading »

Everyone who knows me realizes that I love numbers. To help everyone else in the enjoyment,  I am giving my professional contacts a sneak peek preview of my 2009 third quarter metrics regarding top social media sites and audience demographics.

For purposes of demographic data, variables for such data points are incredibly intense and were primarily deferred to Google’s data repository of browser/site visitors and behavioral analysis. Google has the largest repository of such information and is statistically the most accurate. Additional metrics were pulled from dozens of other sources including Compete, Quantcast, Yahoo, MSN, Alexa and custom research. When outliers created skewed metrics, data was normalized using secondary and tertiary data sources. Continue Reading »