Who’s in the lead? Understanding browser market share statistics: Part 1
You know how fast anything to do with the Internet can change. A new device, browser version, a killer app, or a change in form factor can stir things up in a jiffy. And there are a lot of groups that do their best to keep track of the trends and predict what will happen in the coming months. In the realm of web browsers this is certainly true. Website owners, content creators, web developers and companies of all kinds need to stay up to date on what people are using to access the Internet. That probably includes you.
For instance, just last week Shareaholic published a study on web browser market share with a headline declaring a combination of all Safari versions beat out Firefox and IE for second place in the market. I had to admit the headline had me curious. Safari usually holds a good percentage of the usage because it has to – Apple doesn’t allow any other browser to be set as the default on any of its mobile devices. So even for those like me, that choose to install Chrome on their iPad and iPhone, we are still forced to use Safari when clicking on links in apps or in the built-in email client.
So I read the full Shareaholic report to see how they drew their conclusion about Safari. I agree with their conclusions based on the data they share. But I still had trouble swallowing that Safari had such a large market share. I hadn’t seen any other data showing such a strong increase in Safari numbers. Digging deeper into the latest numbers I found an article on The Next Web regarding the Shareaholic results that points out some disconnects with statistics from Net Applications, another group publishing browser market share data.
Why would there be differences in the statistics, and which one is right? Well, it turns out they are usually all right. That’s why it is so confusing to many people trying to decide which browsers they need to support for their video streaming, website access, or web applications.
Part 2 and 3 of this blog series should help clear up the mystery of whose statistics, or which data, you should believe. Specifically, in part 2 I’ll take a look at why the numbers are often different. In part 3 I’ll offer you some best practices on how to interpret and use the data for your own projects.