Identifying your mobile visitors from web stats

    As mobile browsers have moved from gimmick to the mainstream over the last few years the job of a web developer has had to evolve to service their needs. With full-featured mobile browsers replacing the cut-down early offerings we might have to worry less about our mobile users than we used to but we still have to ensure that they can use our sites with few problems.

    The problem with mobile platforms from a developer perspective is that there are so many of them in use. Testing a web site on the desktop is comparatively easy, once you’ve made it work in IE and Firefox, you’re unlikely to find any issues in Chrome, Safari or Opera so once you’ve given it the once-over on a Mac there’s not much left to do. By comparison it is almost impossible to have one of each of the plethora of mobile phone platforms so once you’ve looked at the iPhone, Android, and Opera browsers, with maybe Windows Mobile and Blackberry as well (assuming you are fortunate enough to know owners of all those handsets) you have little idea how the rest of your mobile users will experience your offering. In my case I have an Android phone and a Series 40 Nokia clamshell, and I borrow a friend's iPhone 3G when I need to test that platform.

    To shed some light on the matter you need to know the scale of the problem. So you go to your web stats or analytics package and look at the browser/OS combinations. If you’re lucky, your package will be capable of recognising smartphones, so you’ll pretty quickly see stats for visitors with iPhones, Android phones and maybe Blackberries. But a cursory glance at the detected user agents should tell you that is only the tip of the iceberg. A quick look at mine reveals a huge list of feature phones, some from well-known manufacturers like Nokia or Samsung and other devices I’ve never seen and in most cases never heard of.
    On my site I finally settled on looking at screen resolutions. I decided anything smaller than 640x480 had to be some kind of mobile device, so added those numbers to those of a few well-known larger-screened devices. The iPhone 4's 960x640 pixel display being a good example. In the end I found that around a tenth of a percent of my site's visitors were mobile users. This was less than I expected because I think the number of different user agents had led me to believe there would be more, however it tallied with the figures for browsers and OSs so I found it to be believable.

A company: "Them", or "It"?

Consider the following phrase: 

"Since it is the market leader it can be assumed that what works in relation to Google will also work for its competitors" 

     Google, like any other company, is an entity. "It". But Google is also a collection of offices full of people. "Them". 
     "Google are writing software that..." or "Google is writing software that..."? My inbuilt English language parser tells me to use the former. Is it leading me astray?

Is there a relationship between content volume and traffic?

    My exercise in future web traffic prediction last month must have caused some interest among its target audience, because I've been asked for more. This time with a twist.
    The question: "If we add a load of extra pages to a web site, what effect will that have on the traffic?". How long was that piece of string again?
    An impossible question to answer. It depends on factors too numerous to quantify and any figures I come up with can't be trusted, I said. We know, they said, but give it a go anyway.
    So I thought about it and decided on the well-known theoretical model of a long tail web site. One with many pages, each of which scores on its own search term and each of which only brings in a few visitors, but when all are taken together the total of all the visits for the site is a very large number. In a long tail site, visits are proportional to page numbers, so all I had to do was work out the average number of visits per existing page and multiply that by the number of new pages for an estimate of the extra traffic.
    My problem was that the figure I reached looked far too optimistic. Believable I guess, but only just. An upper error margin for my new traffic estimate.
   And there lies the fatal flaw in web traffic prediction. As I remarked last time, all I am doing as I go further into the future is giving myself an ever-increasing error bar on my figures. And by adding yet another estimate on top of an existing estimate, all I am doing is increasing that error bar to the point at which the figure becomes meaningless.
    Still, it's an interesting exercise, if only to create some pretty graphs.

A little experiment in hiding words in plain sight

    Yesterday at work I decided to try a little experiment. My desk is next to a busy thoroughfare, with a lot of people who I'd rate as fitting my target audience passing me every day. I printed out a QR code encoded with the phrase "Does anyone respond to QR codes? Email me if you're one of them" and my work email address on a piece of A4 and stuck it on to the office partition facing my passing colleagues.
    QR codes have interested me ever since I first read about them a few years ago. Beyond the steganographic appeal of hiding text in plain sight they offer an interface between printed media and the online world, two areas that seem so mutually exclusive. And since most mobile phones now have the capability to read them they should be far more common than they are.
    Hence my experiment. Employees of a large publishing company are likely to have at least heard of QR codes and also to posses smartphones, but how many will respond to one in their everyday environment?
    I'll be leaving my QR code up for a month. I'll be very disappointed if nobody responds to it.