13+1 problems of web analytics

Almost every day we work with our clients’ analytical tools. We try to guide our clients to use them properly so they don’t lose valuable data unnecessarily. Very often we encounter incorrect setup of the tools, but also incorrect use and wrong view of the data itself. We have selected for you 13+1 of the most common problems we encounter with our clients and partners.

1. Wrong tool connection

The first problem, which we encounter very often with clients, occurs long before the actual data collection takes place. One example is the wrong implementation of Google Tag Manager.

If I don’t insert the code exactly according to the given procedure, i.e. the so-called “script” part of the code in the site header and the “noscript” part of the code just after opening the <body> tag, the tool may work correctly at first glance. However, later you will find that the tool does not run when it should and in some cases does not run at all.In this case, you may lose a significant amount of data. For example, you may not be able to authenticate with Google Search Console or other Google tools.

2. Missing measurement strategy, I measure everything and I don’t know what to do with it

“I would like to start dealing with web analytics, so I’ll put Google Analytics on my website, add some Facebook Pixel, and don’t forget HotJar and Smartlook, because Franta has them on his website too and he said it’s cool.”

Before embarking on any implementation of measurement tools, we should figure out what we actually want to measure and why. It doesn’t matter whether we more pretentiously call it a measurement strategy or perhaps a measurement plan. In the past, web analytics was inaccessible, expensive, and it was complicated to get any data at all. Today, it’s quite the opposite. Today, even an average handy layman can follow the instructions on the internet to set up any tool and start collecting huge amounts of data and information.

How’s it going? After half a year, we have expensive tools full of useless data that nobody in the company even looks at, because there is no time for it, because they don’t know how to make decisions based on the outputs and because nobody knows what to do with it.

The recommendation from us is: “If you’re starting out with web analytics, write down your business goals first. Based on those goals, figure out how your website plays a role in meeting them. Then you can start looking for key metrics to measure. You always need to find indicators that will help you in making further decisions about your marketing activities.

If you’re still not sure, get in touch and we’ll be happy to help you through the initial process of defining your measurement strategy.

3. Missing website objectives

In order to properly define the website objectives, we need to have clear business objectives. This may sound obvious to some, but unfortunately, reality shows otherwise. The business objectives should then be the basis for the objectives the website is intended to fulfill. The easiest way to start is to answer the question:

“What should people on my website do so that their actions lead to fulfilling my business objectives?”

In order to work effectively and regularly with our objectives, we recommend defining no more than 2- 3 main objectives to start with. For an online store, the objective will probably be to ship an order, for a blog it will probably be to read an article. Another goal might be submitting a form, subscribing to a newsletter, visiting a specific page, or the depth of scrolling on a page, for example.

Objectives should be the main indicators of your business, don’t try to cram every potential activity of your visitors into your goals, for example, sub-event tracking can be used for these purposes. Last but not least, don’t forget that each goal should have a so-called Objective Value assigned to it.

4. Missing value of targets

We’ve already said that we need to define the website objectives in order to work properly with web analytics. However, what is often forgotten are the objectives values. You can and should assign a value to each goal in Google Analytics. For more advanced projects, it is advisable that the value reflects the true value of meeting the objective. If you are starting out with web analytics, we recommend choosing any value, you can choose by feel, or for example, assign a value of $1-5 to your objectives depending on their importance.

The value of the goal will open up additional options for you to evaluate your website’s performance. For example, one of the most interesting metrics is “page value“, which is where the value of the objectives met counts. This allows you to better evaluate the performance of individual pages of your site.

5. Only one data selection in Google Analytics

Google Analytics works on three levels, which are account, property, and data selection (view). Today we will focus on data selection, which basically allows us to look at the same data in different ways. Very often we find that we only have one main data selection for a client. Why is this actually a problem? For example, if you select a filter that automatically filters some of the data (for example, a spam filter), you will never see this data again and it is lost. You can easily make a mistake when creating a filter and lose a lot of data.

From our experience, we recommend at least 3 data reports. We use 3 reports. The first one is the Main View, which serves as the main data overview from which we draw data for our routine analyses. The Test View is used for us to test larger interventions and changes to Google Analytics settings. After testing these changes, we only flip to the Main View.  Finally, we create the so-called Unfiltered View, which is simply a backup view of the data that is not filtered in any way, and therefore all the data goes into it in case we lose some of it in one of the aforementioned views.

6. No hostname filter

It’s not a well-known thing, but almost anyone can send you data that looks like a classic visit to your website to Google Analytics. In some cases, this can be a good thing if, for example, someone enters your site using Google Translate. Most often, however, various bots and spammers try to destroy your data. You can check for these visits, for example, in the Audience->Technology->Network report by adding the secondary dimension “hostname“.Therefore, we recommend setting an include filter in the main data report with hostname only on your own domain or subdomains.

7. Incorrect use of UTM Parameters

UTM parameters help us to pinpoint the source of the visit. How and why work with them? A typical example would be a Christmas post with a discount code on our Facebook page. If we don’t tag the link, then in Google Analytics you will only see all visits that came from the link as Facebook visits. So you will never be able to tell if it was just our Christmas post, or if someone clicked through from our company page, or if someone sent them a link to our website in a message.

However, if we tag the link correctly with the appropriate UTM parameter, we are able to find and evaluate visits from just one specific post.

What such a UTM parameter looks like:


What parameters can we use:

utm_source: the source of the visit, most often we choose the web page to which we place the link, in this example it is facebook.com

utm_medium: we can also translate it like “source category”. If you are starting out, we recommend using the standard media that Google Analytics uses, which are for example organic, referal, social, cpc, etc., in this case we chose the medium “social”

utm_campaign: this parameter is used for the name of the campaign itself, you should choose a name so that you are always able to trace each campaign, for this example we chose the name “fb_christmas_camp_20”

These are the basic and mandatory parameters, for more advanced campaign structures, you can add utm_term and utm_content to your parameters, but if you are starting out, I believe you can get by with the basic ones. For easier link building you can use the UTM builder.

In case you are a larger company and your campaign structure is more complex, Archetix can help you set up an advanced UTM parameter structure and make the most of their potential. If you know how to do it, you are able to “artificially” create a virtually unlimited number of additional parameters that will help you in the detailed resolving of your campaigns. If you are interested in this topic, do not hesitate to contact us.

8. Missing or wrong e-commerce measurement settings

This point applies primarily to online stores, although there are specific cases of other websites where e-commerce measurement can be used. The first step is to start actually measuring e-commerce. As a standard, we recommend turning on at least basic e-commerce measurement as a standard, which mainly gives us information about transactions. For more established stores, however, you can’t do much without advanced measurement, called Enhanced Ecommerce (EEC). When implemented correctly, you can get complete information about the entire purchasing process. You’ll see how your customers view individual products, which ones they add to their cart or remove them, how they move through the shopping cart itself, and much more.

However, the most common pitfall is the implementation itself. The truth is that if you use some solutions, such as the Czech Shoptet, then the setup will only take a few clicks. However, for more complex websites, we strongly recommend the intervention of a professional. There are several different ways to implement EEC correctly, and very often we encounter incorrect implementations that cause large data inaccuracies, duplications and meaningless data. It is then impossible to make any important decisions in your marketing based on such data.

9. Measuring e-commerce and working with VAT

We’ve shown the importance of implementing e-commerce measurement (hereafter referred to as EEC) correctly. If we are ever lucky enough to have a client with a technically correct implementation of EEC measurement, it happens that they don’t know what data they actually have at their disposal and how to work with it.

One of the big problems tends to be VAT. It is not possible to say clearly whether we should work with VAT-free or VAT-inclusive prices, this decision should always be based on the overall economic management of our business, but we should always decide on one option and work with that. Very often we see clients combining sales from products without VAT with costs to marketing channels with VAT, etc. In extreme situations, the resulting analyses can also lead to poor marketing decisions and unnecessary losses. It sometimes happens that the extra cost of shipping or various discounts plays a part in this too. Sometimes, they are accounted for, but sometimes they are not.

The matter of properly measuring an e-commerce store becomes a complex discipline as it grows, and it is recommended to take expert advice in these cases. For you, that may be Archetix.

10. Analytical tools are not accounting systems

Often we find that clients imagine that they will get 100% accurate data into their analytics tool. It is true that there are solutions to send all transaction data to Google Analytics, for example, but we have to keep in mind that it is a tool that has its limitations.

It is clear that with the size of the project, the demands on the accuracy of the measured data increase, but you should not forget that Google Analytics is a marketing tool, and therefore I should work with it accordingly. I should take the data as an indicator, monitor trends and compare the benefits of each channel. Make decisions about marketing activities based on this information. We should definitely not expect Google Analytics to replace our CRM system or internal order management system.The recommendation from Archetix is. Learn to mine the best quality data for marketing management to the extent that the data itself can give you a weighted result. Don’t throw dozens of hours into complex implementations for the sake of 1% data refinement, but rather focus on how to analyze the data you get and use it effectively.

11. User identification

A user is not really one person. A user is actually one device, or one browser, or better yet, one cookie. So we can’t tell if it was one person sitting at a computer, or if it was a computer in a school library with a hundred people in a day.

Similarly, we will not recognize that person who has deleted the cookies in their browser. We can’t even tell if one person visited our website at work on a work computer and later at home on a tablet.

But there are ways to help us refine this information. One solution may be to measure logged-in users who identify themselves by email, for example. However, if your website doesn’t offer this option, it’s almost impossible to measure my customers’ behavior across different devices and we shouldn’t worry too much about it.

The recent trend is to move towards “Customer-Centric” Analytics, where everything is related to the user. A new tool, Google analytics APP+WEB, called Google Analytics 2.0, is also going this way.

So today, we should be focusing on how to intelligently guide users to log in and how to ensure that they are logged in every time they visit. Archetix will definitely be happy to help you with this.

12. Most of my visitors are from Prague

Beware of very distorted data on geography. Google Analytics only distinguishes geographic data based on the so-called IP address and not, as one might think, on the GPS location of our phone.

What does this mean in practice?

For example, most visits from mobile devices that are connected via mobile data are reported to us from Prague. A large number of internet suppliers will in turn report from large regional cities, even if you are connected in a remote village. Corporate networks often use a uniform set of IP addresses for all their branches, and it may happen that a user who connects from the Pilsen branch will be seen in your analytics as a visitor from the headquarters in Berlin.

Therefore, take geographic data with a grain of salt and use it only as an indicator. Across countries, they work quite well, but it is still a good idea to combine them with the language of the visitors, for example. The data on cities is very imprecise and we recommend excluding Prague, for example, from the analysis altogether.

13. Do I have a good Bounce Rate?

Bounce rate, or the rate of immediate abandonment. This metric is highly debated and in most cases highly overrated or misused.

The truth is that bounce rate is a very useful metric, but we need to work with it properly. The most important thing is to look at what landing page I’m measuring bounce rate on. And before that, it’s important to know how the bounce rate works in the first place.

If a visitor comes to my website, does not take any action and leaves, then a so-called bounce visit is recorded from which the bounce rate is then calculated. However, unless I set Google Analytics otherwise, only clicking on a link that points to another site of the web is considered an action. So if a visitor comes to my recipe website, after searching for a recipe for sirloin steak, reads my blog article with the recipe and leaves, then his visit is recorded as a bounce. But the visitor did accomplish the goal of my website, he read the blog article. In that case, the resulting bounce rate doesn’t make sense.

In these cases, there are several solutions that can, for example, select scrolling on the page as an action. At this point, the visitor already takes an action by scrolling down my article and then it makes sense to deal with the bounce rate. However, this is a more advanced implementation that we recommend consulting an expert.Overall, we can say that bounce rate is a metric that should serve primarily as an indicator of problem areas on our website and we should definitely not focus on it. We recommend focusing on its outliers (i.e. low values below 10% and high values above 90%) and checking the landing pages where these values occur.

BONUS Missing documentation

The documentation is known and often used mainly by programmers. However, it is not common practice to keep documentation for the settings of analytics tools such as Google Analytics or Google Tag Manager.

What is the purpose of such documentation in the first place?

The documentation describes and stores information about all the settings of individual tools. It describes the individual settings, accesses and account structure.

Let’s take a look at an example: I come as a new marketer to a medium-sized company that runs an online store. Among other things, I take over the management of Google Analytics, where I see that a kind of an info mail has also access to the account. Of course, nobody in the company remembers why this e-mail account has access to our data, maybe Jimmy would know, but he doesn’t work for us anymore. Of course, we can’t delete it, because what if some advertising system is connected to it?

For these purposes, we recommend keeping complete documentation of all the tools you work with. This has worked well for us several times and saved us many hours of work. Archetix can help you figure out how to maintain such documentation, how to work with it efficiently, and also, for example, how to structure your accounts and tools correctly.

Scroll to Top