Web Analytics are an important factor in the health and performance of a website, but online marketers often get too involved in the complexities and details, forgetting that the numbers they are seeing might not be 100% representative of the activity taking place on their site. Here are some common misconceptions that you might want to think about:
1. Web analytics systems are always objective
We tend to assume that the numbers that appear in web analytics reports reflect visitor behavior. For example, if the reports say that a visitor spent eight minutes reading a page, we just assume that a real person spent eight minutes reading that page. But how can you be sure? All we really know is that a computer requested the page for a certain length of time, and that the same computer requested a different page two minutes later. With some web analytics systems, you don't even know if it's the same computer, you only know that it's the same IP address. We make many assumptions about the nature of what is going on at this end, but we don't really know for sure.
Let's use bounce rate as an example. A bounce is defined as a one-page visit. We assume that bounces are people who arrive at a website, don't find what they want, and then leave without ever entering the site. Therefore, the assuption would be that bounce rate is supposed to tell us how many people didn't like the site.
However, when labeling a visit as a bounce, web analytics systems do not take into account how long someone spent reading the page, or whether they came back again later on. If somebody spends ten minutes reading your homepage, does that really suggest they were not interested in your site? Or the other way around, if they spend 30 seconds on the page, then come back a few hours later for an hour, can you really say the site was of no interest to them?
It's important to keep in mind all bounces are not bad. Some things that cause high bounce rate are:
* Links to external sites that you want visitors to click on
* Ads on your site that take visitors away from your site
* Returning visits might bounce because they might come to your site to read your daily/weekly/monthly update or a single blog post
* Visits that are for a specific reason e.g. to find a company phone number and once they have found it they are happy
2. Web analytics systems are always accurate
There are several ways in which people navigate websites which are either not tracked or misleading - for example if a user leaves a site by repeatedly clicking the back button to reverse their path. This means many visits end with a series of one- or two-second pageviews which can increase the average number of page views per visitor, and reduce the average time spent on page.
Another good example is time spent on site. There are many concerns with measuring the true time spent on the site or page. One of the main reasons is that time spent on the last page that a user views/reads is not calculated. So if you have a non-ecommerce site then chances are that a visitor will spend most of their time reading the last page but that page will not be counted, and therefore your time on page and time on site metrics will be way off.
Anything that is an average could also be misconstrued. For example, if you have a major spike or dip in your traffic one week. This could totally skew your averages and give a false impression of the performance of your business.
3. Web analytics systems are comparable
Because there are different ways to collect raw data, each of which has its own particular strengths and weaknesses, different systems will measure different things but report them as the same. Because of this, two web analytics systems will rarely report the same figures.
4. Web analytics systems give you the whole picture
Getting visitors to the site is the first step. The next step is to make sure you have content that is going to give them what they want. Analytics can help with this, but once visitors fill out the contact form, what happens next?
How many decisions are made by looking at top level analytics alone? Someone has to tie leads back to the website to determine what is working and what isn’t.
For example, in a business-to-business situation, a whitepaper download may bring in lots of leads, but none are qualified. Or maybe there is a call to action form that is bringing in few leads, but they convert really well. Analytics can’t tell you what happens with a lead after filling out a form, and connecting that data is very important.
5. Once set up, web analytics is easy
It’s not really something anyone can do in an hour a day. If website marketers really want to get valuable information out of analytics, they need to invest time and resources in order to make that happen.