Every business that has a website should keep track of its analytics in order to improve traffic and improve sales. However, having graphs and reports from web analytics is not enough. The information needs to be interpreted correctly so as to benefit your business. Drawing the wrong conclusions could have very detrimental effects.
Here are some of the common web analytics mistakes you need to avoid:
#1 Confusing views with visits
Though many people think of views and visits as one and the same thing, they are very different. When someone lands your site from an external URL, it is referred to as a visit. Regardless of the number of pages they visit when on your site, it is only counted as one visit. The visit ends when someone closes their browser, goes to an external site or remains inactive for a long time. On the other hand, a pageview is counted every time a browser loads or reloads a page on your site. Therefore, if a visitor lands on your site and visits seven pages, it will be counted as one visit but seven views.
#2 Visualizing your data incorrectly
Visualizing your data makes it easier to present web analytic results to your audience. However, when you use the wrong visualization methods, you will only end up creating confusion. You need to ensure that your data is represented using the right kind of chart of graph. For instance, if you want to show the geographical locations of visitors, it would be advisable to use a pie chart. If you want to communicate progress over a period of time, then a bar or line graph would be ideal. The good news is that there are a number of dashboards and SaaS providers that allow you to view your web data at one glance.
#3 Clustering all the traffic together
People visit your website through a wide range of marketing channels including social media, organic search, email marketing, paid traffic and referrals from other sites. However, you should never make the mistake of placing all this traffic in the same category. If your site receives 12,000 visits in a particular month, be sure to break it down into different categories representing the different channels. How much did you receive from email? How about social media? How are the numbers varying from one month to another? This information will give you an idea of where to invest your resources in order to generate more traffic and conversions.
#4 Incorrect comparisons
Making incorrect comparisons from your web analytics might cause you to make the wrong conclusions about your business. For example, when you compare January and December of the previous year, you might find yourself getting worried about the drop in sales. However, the reality is that people buy more during the holiday season. Therefore, there is really no cause for alarm. It would, therefore, be more realistic to compare January with January of the previous year. Take note that your website traffic and conversions could also fluctuate due to other reasons such as political events, weather or changing business environments.
#5 Misunderstanding numbers
When it comes to web analytics, low numbers should not always be a cause for concern. For instance, if you have a low email unsubscribe rate, it means that your audience is deriving value from your content. If your customer acquisition costs are getting lower, it is an indication that your marketing strategies are working well. In addition, low numbers can show you where you should be investing most of your time and resources. For instance, if Twitter is generating more conversions than LinkedIn, it would be advisable to focus your marketing efforts on the former rather than the latter.
#6 Failing to distinguish marketing qualified leads (MQLs)
When it comes to web analytics, you need to distinguish between ordinary leads and marketing qualified leads. Leads are just curious about your service or product, and might even fill out and submit a form on your site. However, MQLs are not just curious but are actually contemplating purchasing what you are offering. Different companies qualify leads in different ways. For instance, someone could be considered an MQL when they sign up for the free trial. Therefore, when presenting your analytics report, don’t make the mistake of clustering ordinary leads and MQLs together.
#7 Including internal website visits
Every day, business websites are visited by people who are directly associated with the company. This could be web developers who are maintaining the site, or company staff that are looking for information. Including such visits in your web analytics can skew your data and give the wrong impression. Therefore, to avoid this, you will have to exclude the IP addresses of everyone that is a part of your company. The good news is that there are IP filters that can help you exclude such addresses.
#8 Assuming more time on page is equivalent to greater engagement
Most people assume that if a visitor spent a lot of time on a web page, it means they engaged much with their content. While this might be true, it is not always the case. At times, visitors stay on your page for a long duration because they cannot locate what they looking for. This means that the usability of your site needs to be improved. Therefore, before jumping to conclusions, it would be advisable to carry out user testing to find out if visitors actually engaged with your content. You should also look for ways of enhancing visitor engagement on your site.
#9 Failing to come up with actionable takeaways
It is a fact that many marketers use data from web analytics merely to create reports that are presented to their bosses or team members. However, just presenting raw data on leads generated and web traffic does not help much. You need to derive actionable takeaways that can be used for improving your marketing campaigns. For example, if your results show that your email marketing campaigns are more effective than social media, you could consider investing more resources into email marketing.