One of the first things I learned when I dug into web analytics, was that no two packages are alike. Sure, the names may sound the same (e.g. visits) but the way that the software measures these units could be completely different. One package may obtain its data from a cookie; another off a log file. Most casual users don’t understand this, which often results in huge misunderstandings to very basic questions.
Take “hits” for example. I cannot tell you how many people I’ve talked to who focus solely on “hits” to their website. The challenge with looking at “hits,” is that a single hit can mean a lot of different things. Are they page views? If so, do they include non-human occurrences like search engine bots or spammers? If they’re visits, how are they being measured? Some packages allow the end user to customize what a visit means. So, a “hit” on your site may not mean the same thing as a “hit” on someone else’s.
Unfortunately, hits are misleading. If you’re worried about what people are doing when they come to your site, you really need to look at multiple metrics rather than hang your hat on one–especially if you’re looking at a way to measure and improve your website’s performance.
As you can imagine, web analytics can get pretty complicated, but it doesn’t have to be. The biggest trick to understanding your visitors, is to look at trends rather than individual data points. This is especially true when it comes to data points like keyword or search engine referrals; remember, the purpose of web analytics platforms is to track a three-dimensional visit to your website or blog. Translation? One visit results in several different types of metrics including:
- How did your reader find your article? (e.g. direct or referred traffic?)
- When was the last time they visited? (new versus returning)
- How many articles did they read? (average page views)
- How long did they stick around? (time on site)
- What page did they enter my site?
- Do new visits coincide with my published content?
Here, the specific data points aren’t as important as the questions you are trying to answer. Of course you’re worried about how popular your website is, but your presence online is also related to why someone visits your website. Someone could come to your site by mistake or because they typed in a particular keyword. Others, from a bookmark or a link on a popular website. If you look deep enough, your data will show you what you need to see. Digging deep into web analytics allows you to understand your traffic from the ground up. Once you’re on the top floor, you’ll know exactly where to look when you’ve got a burning question to answer.
To get a handle on your data, ask yourself what you want to know about your website. Compile a list of questions and see what data helps you find the answers you’re looking for. Then, start comparing and contrasting your data over different periods of time to see if a pattern emerges. For example, check out weird spikes or volleys in traffic. Can you figure out what happened?
In many ways, analyzing web analytics is a lot like putting a puzzle together. Individual pieces may or may not be important by themselves, but together you can get a clearer picture of what’s happening on your website so you can make adjustments that matter.