Are you addicted to data?

 

When deciding on a measurement strategy for Analytics, it's easy to fall into the trap of thinking you need to measure everything "just in case you'll ever need it”. Below, I will describe the mess that this strategy can get you in, and what you can to do to get out of it.

For long, the ease of collecting data that us implementation specialists have been accustomed to, and which we've happily showed-off to our clients, made it easier to track everything rather than think beforehand which data you would actually need.

Collecting data can become quite addictive, especially once you realize that the possibilities have been steadily growing, and today are nearly endless. The often mocked and somewhat underappreciated computer nerd (Yes, I’m painfully aware this is a reflection of a younger me 🤓) might see this newly acquired power and want to use it to the fullest, ”just to show them once and for all what we can do”!

it seems that everyone else is simply gathering as much data as they can, and if you don’t do the same you will be long gone

On the client side, I think there has been a dash of the FOMO, since ”Big Data” have been the hype for the last 5 years, and it seems that everyone else is simply gathering as much data as they can, and if you don’t do the same you will be long gone.

The Risks of Data Addiction

It’s easy to think that more data is always better, since this allows you to hoard data and then go back and fetch it once you figure out what data you actually want to look at. However, it’s harder to see the risks that this approach includes. Three of the risks you may encounter are the following:

Risk 1: Over-collecting

The first risk is that you may in fact be collecting data you are not allowed to store. Personally Identifiable Information (PII) is a hot topic and not managing your data collection carefully may lead to you collecting information that by itself does not look like PII, but linked with other pieces of collected data in fact builds up information that can be narrowed down to one person.

Risk 2: Technical debt

The second risk is the risk of technical debt. It’s important to realize that every data point you are collecting needs a script to execute something on your site and send something to your data collection platform. Noted, these are usually very small and insignificant on their own, but everything adds up, and if your website is constantly changing you may end up in a loop of constantly needing to update your tracking scripts to keep up with your website.

Risk 3: Distractive data

The third risk is an even more hard-to-spot risk, since you usually don’t see it before it’s too late. There is a saying that you sometimes can’t see the forest for the trees. Similarly, your analytics tools may end up so densely packed with information it’s hard for you to distinguish real insights from merely distractions.

Conclusion

The rapid development of tracking technologies and abilities have somewhat gone to our heads, enabling us to collect more data than we really need, simply ”because we can.” This approach may seem like the sweetest dream at first sight, but may taste more bitter than we anticipated.

I do want to close this piece off with making really clear that I LOVE DATA! There is nothing wrong with collecting data, and in some (nowadays quite rare) cases, I do come across clients who do not track enough data. So, don’t read this piece as a ”data is evil, and we should not be tracking anything” statement, because it is quite the contrary.

Keep tracking, but make sure you know what you’re tracking and why! (BTW, a strong Measurement Plan will be really helpful in this sense!)