Most Common Mistakes Made with Web Analytics Data
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#1 Mistake: Reading your data as a WHOLE.
This mistake is a rookie mistake made by almost every company when they first decide to implement some type of analytics package to their company website. Breaking down the total analytics package into smaller, more manageable sections allows you to focus in on certain areas.
For example, taking your Analytics Device page from your Visual Visitor dashboard (or other software package if you are not currently using Visual Visitor’s Anonymous Visitor Identification software), you will notice that you are not given just one piece of device information. This information is broken out to Top Browsers, Unique Visitor by Browser Family, Top Operating Systems, Unique Visitors by Browser Version, Visitors by OS Family, Visitors by Device Type, and finally, Visitors by Browser Resolution.
Just taking the first chart, Top Browsers, would be better than nothing, but it wouldn’t give you the entire picture of your visitors.
Knowing that more visitors are using Chrome than IE makes a big difference in your website design, as does knowing that the majority of your visitors are still using IE version 11.0. This data enables you to view your site as your majority of visitors does because let us not forget, not all software versions are going to run the scripts on your site the same.
#3 Mistake: Confusing a Visit with a Page View
What? Isn’t a visit a page view? Actually no, not all visits are page views – and this is a common mistake made by so many that are tasked with the actual reading of the analytics data.
A visit is when someone comes to your site either through an external link or URL, or by coming to your site directly by typing in your url. This visit can consist of multiple page views and Visual Visitor will track those page views by visitor, or it can be a bounce in which the visitor comes to just the one page and then leaves.
#4 Mistake: Underestimating the Bounce
A bounce is when a visitor has just the one page view – and can tell you a lot. So many times when I ask the question, “What does a bounce tell you?” I get the answer, “An accidental visit.” But there can really be a lot more to it than just that.
Take it on a page level, a high bounce rate for a page can actually be an indication that this page is not loading properly. So further analytics data is necessary. Example: what if when researching a high bounce rate for your pricing page shows that you also have a high percentage of users using safari? One simple solution to understanding this high bounce rate would be to simply log in using the software version of safari – you might find that it is not loading properly causing people to discount your product and move on. This would be missed if you just ASSUME that the high bounce rate is an accidental visit.