Having a website doesn’t mean sitting back and waiting for the money to come pouring in. A website is not a static thing, it requires constant updates and improvements.
But how do you know what changes to make to improve your website? The answer is simple: web analytics. With web analytics you can determine what works and doesn’t work on your website.
Web analytics starts with statistics: numbers, percentages, and graphs. You need to understand the basic elements of web statistics before you can graduate to proper analysis of those figures and derive actionable insights from them.
In this article I will try to explain the basic terminology of web statistics. Different web analysis programs sometimes use different wordings, but you will be able to recognize them and interpret them accordingly.
Web statistics terminology
- Unique Visitors: this is the first statistic many rookie web analysts look at, but in my opinion it’s one of the least important numbers. It refers to the number of individuals that have visited your website in the given time frame. It is always a rough estimate as due to the limitations of web technology it’s nearly impossible to accurately determine how many people actually see your website. The raw figure is not that interesting, but as a trend over time it’s worth keeping an eye on, especially if you have initiatives running to draw more visitors to your site.
- Total Visits: this figure indicates how many times web users have visited your website. The same user can come back to look at your site again within the set time frame and will generate two or more visits to your site. This metric combined with unique visitors determines the stickiness of your website. It’s sometimes also referred to as sessions.
- Page Views: this metric indicates how many pages of your website have been shown to visitors. Don’t be surprised to learn that many visitors only look at one page of your site and then leave. Some visitors will click through to other pages and log multiple page views in your statistics. Combined with the total visits this gives you the average page views per visit, which is an indication of how engaging your site is.
- Hits: a remnant of the old days of web statistics, a hit is every single request a browser sends to the web server your site runs on. Every single separate element of a web page, including the HTML file, CSS stylesheet, and all the images, generate hits when someone views the page. These days it’s a fairly useless number, as any given web page can generate anything from one to fifty hits.
- Time on Site: this indicates how long an average a visitor has spent on your website before moving on. This can be a difficult statistic to use. If for example you have a blog, most of your website’s visitors won’t go beyond the homepage. This means your web analytics program probably won’t be able to see how long those visitors actually spend on your site, as they undertake no action that can be logged. It will count all those visits as zero seconds long, regardless of how long the user spent reading your content.
- Bounce Rate: this metric is usually attached to a single page on your website. It shows the number or percentage of visitors that saw only that page and then left shortly thereafter (usually within 5 to 10 seconds). For some reason those visitors clicked the back button, closed the browser window, or went to a different website immediately upon entering your site. This can have many different causes, but generally a high bounce rate on a page means that page isn’t very appealing and can use some improvement.
- Exit Rate: similar to bounce rate but also different in a very fundamental way, this metric indicates how many people came to a page on your website and then left. This goes beyond bounce rate as it counts those users that navigated through your site prior to exiting. Some pages should have a high exit rate, like for example the “Thank You” page after a submitted order.
Good web analytics programs calculate the exit rate while omitting the bounces shown in the bounce rate, so you will get a good sense of where your site’s engagement with its users fails.
- Referrals: this is not a number but a list of sources of visits to your site. This contains everything from the search engines people used to find your site to links on other websites that users clicked on to get to your site. Ideally your analytics program should also tell you what keywords users typed into the search engines to find you, and on exactly what page of an external website the link to your site was found.
There are other statistics worth looking at, such as the error codes (especially the 404 error) and visitor origins. But the metrics listed above are the core measurements that you need to have a good grasp on to gain valuable insights into user activity on your site.