I frequently see accounts with over 100 tracking tags dedicated to web analytics. Or even bizarre requests for tracking every single click on a link in the footer. The desire to become data-driven has led many companies to believe that they need to track everything, often without a clearly defined objective. So, here are 7 reasons not to fall into the trap of overly exhaustive tracking.
1) The analytical capacity of companies
To begin with, it’s essential to understand that not all companies are equal in their capacity to analyze data. Even though many of them use the same web analytics tools, like Google Analytics, Piano, Matomo, or even Piwik Pro, their websites and aspirations are still very much unique. This is why it’s important to develop a tagging plan that aligns with the objectives, but also with the analytical capacity.
A marketing team of 2 people won’t have the same needs as a team of 4 web analysts. Hence, build tracking that is on par with your resources, no more, no less. Don’t forget that collecting large amounts of data without having the skills or the necessary manpower to analyze its results in wasted effort and resources.
2) The irrelevance of some information on a site
Another argument against total tracking is the irrelevance of certain information collected on a site. Consider this: every tracked element on the site must be linked to a specific objective. Objectives could be related to business (revenue), marketing (newsletter sign-ups), or sales (number of calls generated from the site). If an element doesn’t have a clear connection with an objective, its relevance can be questioned.
For example, the time spent by a user on a specific page might not be useful data if the goal is to track conversions or improve click-through rates. Conversely, this data can be extremely interesting for a blog site that aims for a complete reading of the offered articles.
To avoid getting lost, it is crucial to define the KPIs (or key performance indicators) even before you begin tracking data. This will help identify essential data and focus on metrics that matter. By keeping the focus on business objectives, companies can safeguard against the risk of collecting useless data … and wasting time analyzing it aimlessly.
3) The risk of misinterpreting data
The massive accumulation of data can also increase the risk of misinterpretation or overinterpretation of data. Companies may be tempted to find patterns where there aren’t any, which can lead to incorrect decisions.
For instance, if a company tracks all user activities, it may see a correlation between two events that in reality have no connection. This could lead to strategies based on false assumptions. To avoid this syndrome, I always advise my clients to visit their web analytics tool only after identifying a need and/or a hypothesis. This allows you to start from the problem and try to solve it through the data and not the other way around.
To conclude on this point, data overload often leads to situations where companies are overwhelmed by a tide of irrelevant data, obscuring the truly useful and actionable information. This pushes either to bad decisions or to inaction… which is also a bad decision!
4) The importance of data quality over quantity
It can never be said enough: it’s better to have 2 quality indicators than 50 useless ones.
Data quality is much more important than quantity, and tracking everything on your site often means sacrificing one at the expense of the other. It’s therefore necessary to construct a solid and well-thought-out tracking strategy that focuses on acquiring relevant data.
But if the strategy is essential, the operational part is equally important. Focusing on important indicators will simplify the setup of tracking and potentially limit errors that could lead to wrong interpretations. If the initial setup is of crucial importance, regular control procedures and updates of tracking in line with website developments also need to be put in place. The more indicators there are, the heavier this process can be!
So, remember that the goal is not to have the most data possible, but rather to have the most accurate and relevant data while ensuring that their collection remains functional.
5) Web performance
The website loading speed (or web performance) is an important issue, extending beyond technical considerations. Search engines and marketing platforms want to provide their users with the best browsing experience possible. That’s why a slow website can be penalized both in terms of organic and paid search rankings.
While tracking will not be (in most cases) the number 1 reason for a site’s underperformance, it can contribute to it. Don’t forget that your various tags on GTM are in reality scripts, and the more you multiply them, the more they will affect the site loading time.
There are solutions like server-side tracking that can help mitigate this issue. By shifting some of the tracking work from the client side to the server side, you can reduce the number of scripts on the page and improve performance. However, even with server-side tracking, there will always be a base of browser-side tags. Thus, overly exhaustive tracking will always impact loading time, although this will be mitigated.
6) The costs of keeping up-to-date
I often say that tracking is not a project, but a department. This may seem exaggerated depending on the structure and maturity of the organization, but the idea is that tracking is never set in stone. I’m always amazed to see Google Tag Manager accounts with no modifications in the past 2, 5, or even 7 years… Does this mean the website has not evolved during this period? It mainly means that tracking hasn’t been integrated into the company’s web evolution processes.
Each development of the website can impact the current tracking in place, but new features should potentially also be tracked (if necessary and linked to an objective). This is why the heavier the tracking, the greater the maintenance efforts will be, necessary for data quality.
Therefore, you need to plan for this workload, whether it’s handled internally or outsourced through an agency or consultant. This will have an impact in terms of operating costs.
7) Tool costs
If you use technology like server-side tracking, know that the volume of requests going to your server will determine the operational cost of this technology. This is why the denser your tagging plan and the number of events measured, the higher the costs could potentially be. This will of course be correlated with the volume of user interaction with these same events.
The same problem and consequence come with using a data storage solution. Take the example of Google’s data warehouse: BigQuery. You might want to go beyond the interface of your web analytics tool and use a tool that allows you to run SQL queries directly on the database. This is very powerful because you could cross-reference data, which is sometimes complicated in the UI of Google Analytics, Piano, or others.
But the cost of a solution like BigQuery will depend on the volume of stored data. Once again, the more events you have, the more it will cost you.
Conclusion
Tracking is an essential component of a company’s digital strategy. When used correctly, it will provide valuable information that can help guide decisions and improve performance. However, the temptation to track everything can create more problems than it solves. That’s why, instead of wanting to measure everything, it’s better to adopt a more targeted approach and only track data related to objectives.
Lastly, it’s essential to remember that tracking is not an end in itself. It’s merely a means to help you measure user interactions. The goal is not to collect as much data as possible but to obtain the most accurate and useful ones to achieve your objectives.
