Nearly everyone who talks about the differences between designing for desktop and mobile talks about how you have to keep in mind that your users are “on the go.”
How true is that? How often are people walking fast down the street looking for a crucial piece of information vs. sitting on the bus, at their office, or on their couch using their phones?
Using a combination of the accelerometer and GPS, we could define some metrics as to whether or not the person is stationary or moving. We might be able to tell if they are sitting (little accelerometer movement) but in a vehicle (GPS changes).
That’s information that goes far beyond the traditional page view or user session and into information that is mobile specific and very useful for user experience designers.
I realize there are both privacy and battery life concerns with tracking this information. It isn’t a simple problem to solve.
But if those obstacles could be overcome, understanding whether or not our visions of how people “on the go” use mobile technology matches how people really use their mobile devices, would be very interesting.
Image courtesy Flickr user rustmonster licensed under Creative Commons.
I’ve been helping a customer try to understand their web statistics. They get reports from AWStats, Google Urchin and Google Analytics. Needless to say, they are confused by different numbers each system gives and want to know which one is right.
People often want the following two things from web statistics:
- Some sort of industry benchmark that is a fair comparison to their site so they can tell how their site measures up.
- Absolute truth in web statistics instead of approximations and interpretations.
The reality is that they will never get either one.
Page views and visitor sessions are interpretation of what happened on a site. Every analytics package measures these slightly differently.
The only statistics that matter are your own statistics. You have to measure your site consistently, make improvements to the site, and then see if the improvements result in an increase in your key performance indicators.
Think of web analytics like runners measure their personal best times. Day-in and day-out, you’re measuring yourself against your time yesterday and trying to get better. What your competition is doing doesn’t matter nearly as much as improving your own performance.