Woohoo! We had a great time presenting at eMetrics this week. The presentation was about the different ways that you can monitor web performance and how it really impacts the bottom line (how you can avoid losing money!). Enjoy 
(I wrote up a detailed outline of this at Bitcurrent.)
I attended a panel on crowdsourcing support at the SIIA Software Summit. The panelists had some interesting statistics on what the crowds within an online support community are like, and what they look for.
This happened over a period of 6 years, and the company invested heavily in things like member recognition. Ultimately, community members with high rankings were able to use this on their LinkedIn profiles, because it’s a sign to potential employers of that person’s expertise and ability to work with others.
Ultimately, support communities are one of the most popular, visible sources of community ROI. But expect to change the metrics you track as they mature and as the goals you’re after change.
Sean and I go live in San Francisco in a few minutes. While the preparation has been great, and we’re expecting a decent audience, today’s breakfast was an ominous message from the kitchen.
Some success with the arts & crafts section. The presentation saved as a PDF.
We’re doing a presentation that’s excerpted from the book at DemoCamp Guelph tonight. Should be an interesting conversation; we have an “exercise” planned. Sean can’t be here (he was at Podcamp and has to get real work done after a weekend of editing the 400+ figures in the text!) but will be joining on Twitter. If you have photos from the event, or questions for Sean, we’ll be using the #CWM hashtag (for Complete Web Monitoring, the title of the book.)
One of the projects we’ve been working on is trying to create a single, comprehensive overview of the Complete Web Monitoring process. Here’s where we’re at (and an early glimpse at a poster we’re working on.)
First of all, a complete monitoring strategy includes the many questions a web analyst needs to answer:
Any strategy also has to look at several different stages in monitoring:
If these look somewhat like Dave McClure’s Pirate Metrics, it’s because he’s awesome and we borrow heavily from his thinking on startup metrics. Anyway, this PDF is a work in progress of trying to align the big questions analysts need to answer with the various stages of visitor engagement. Once we sex it up a bit, we’ll make some posters.
I’ll put the DemoCamp slides up here shortly.
I presented the first Watching Websites presentation at PodCamp toronto on Saturday, February 21st. I got off to a slow start, but found my wind about 10 minutes into the presentation and slammed the 80+ audience members over the head with different ways to measure their sites. Overall, it went really well, and we got lots of great comments from the presentation. Also, the slidedeck was featured as “Presentation of the Day” on slideshare! Nice!
Anyways, here’s the presentation, without annotation.
You can reach Alistair on his Twitter feed or me (Sean) on mine if you have any questions.
Enjoy!
I have a problem with web analytics.
The whole notion of a web visit as a rigid set of steps that users follow is incompatible with how we use the web today. Visitors browse around the site, taking their time, exploring and interacting. Occasionally, they complete some kind of action we want—inviting their friends, buying something, and so on.
For a couple of years, I’ve been thinking about web visits in terms of two fundamental building blocks: Places and tasks. If you look at your site as a series of places and tasks, you’ll think differently about how and what you should be watching.
Uh oh. Is the site is down?
Yahoo! site inaccessible
Site downtime is rare these days, but it still happens, and when it does, thousands of people can be affected. But how do you know that an entire web property is down, and that it’s not just down for you? How can you figure out who’se affected by the outage?
I’m currently in the middle of writing the Web Analytics chapter for the book, and my gosh - things have changed so much in fifteen years. This screenshot is from the program “GetStats”, one of the first web analysis tools to exist. I ran it using watchingwebsites.com logs (I had to parse them through sed & awk to change their log format to CLF for it to work). Notice how it took 7 and a half minutes to process as many lines!
I was talking to the author, Kevin Hughes about GetStats and the state of web analytics when he first wrote it. “Actually getstats wasn’t the first Web server log analysis tool, but it was very influential in terms of the way the data was presented and summarized. Roy Fielding with wwwstat was the first as far as I can recall to present statistics in an easy-to-read paragraph summary form, that I think was written in Perl. I also took ideas from Thomas Boutell (wusage) and Eric Katz (WebReport).”
Web analytics tools began by telling us how many hits we had on the site, but that doesn’t do much today to tell us what’s really happening with our sites. The tools went through many evolutions before they got to where we are today - simple metrics, a few KPIs and actionable information. I’ll touch a bit on this in the book; we’ll also cover implementation methods, advantages, limitations and deployment impact of web analytics tools.
The book is days away from having a completed 1st draft. I can’t wait to send the complete manuscript out to the reviewers!
