Are you here looking for all of my blog posts about web analytics? (Because you can find them at the end of that link.)
Assuming you’re after some more generic information about me, web analytics, and our history together: this is where the magic happens.
I currently work as a Senior Analytics Strategist at an interactive agency in the SF bay area. I’ve been doing web analytics for several years now and I’m perhaps a little bit embarassed by how much of my spare time is spent thinking about it. Particularly by how many mornings I wake up with a first thought that’s somehow analytics-related. On the other hand, this is the way my brain works when it’s churning through a big problem, or system of problems. Luckily analytics is a HUGE system of problems, so I think I’ll be occupied with this for quite some time.
These days I’m combining two of my (seemingly unrelated) loves: web analytics and digital audio. See, the thing is, since people do things in weekly patterns, analytics data often turns into a periodic waveform. If you can get hourly data, even better–daily periodic waveforms on top of the weekly periodic waveforms. Guess what music is? Periodic waveforms. Just take a look at an audio file in any audio editor and you’ll see that if you zoom in enough, some similarities start to show up with the graphs you’re used to seeing in your analytics dashboard. That’s…nice, I hear you thinking. But what if we could listen to the analytics data? What would it sound like? Would our ears be able to get something out of it that our eyes don’t? Would it be useful? What data should we feed it? I asked my brother Adam, who is truly a rock star among nerds, to help me out with a little application that could convert CSV files into WAV files. That way I can rock and roll all over Excel and then listen up.
In the recent past, I have also done the following actual job-related analytics things:
- Built a model for a Fortune-500 company that predicts their day’s total online sales to within 7% of actual by 9 a.m. every day of the week except for Sunday. (Sundays are weird and make you wait a little longer.)
- Built another model that predicts the week’s online sales by EOD Tuesday to within 10% of actual 90% of the time. (“Sixty percent of the time, it works EVERY TIME…”)
- Developed a data-mining methodology (in Excel!) that allows me to easily compare hundreds of variables visually and find correlations and predictive relationships, with the option to sort data by day of week (which is something I simply do NOT know why analytics packages are not doing automatically)
- Created a new funnel visualization that gives more related data than any package’s funnels do
- Taught Web Analytics Association Basecamps (Web Analytics Overview and Online Campaign Optimization), and moderated eMetrics panel sessions
- Conducted analytics assessments of bajillions of sites as part of my agency’s initial strategy phase, and then measured improvements after we launched with new designs
- Spent an inordinate amount of time measuring video on Flash sites. Seriously. There are fancy solutions out there for this now, but back in the day it was just me and the Flash programmers figuring out standards for tracking video viewing, completion, dropoff, etc…and let’s throw in that when everything is Flash, concepts like “page views” are completely useless, which means that concepts like “bounce rate” are pretty useless, which means you’re starting from scratch in general.
- I can out-Report-Builder Report Builder. Too bad HBX is so totally last season. I have yet to see Omniture’s new SiteCatalyst replacement solution but I’m anxious. I’m also really excited to see what people come up with for Google Docs (or even Excel) and the new Google Analytics API…if someone builds a Report Builder thingamajig I will personally hug them.